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Zhao W, Zhang Y, Lim KM, Yang L, Wang N, Peng L. Research on control strategy of pneumatic soft bionic robot based on improved CPG. PLoS One 2024; 19:e0306320. [PMID: 38968177 PMCID: PMC11226027 DOI: 10.1371/journal.pone.0306320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 06/14/2024] [Indexed: 07/07/2024] Open
Abstract
To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot.
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Affiliation(s)
- Wenchuan Zhao
- School of Information Science and Engineering, Shenyang University of Technology, Shenyang, China
| | - Yu Zhang
- School of Mechanical Engineering, Shenyang University of Technology, Shenyang, China
| | - Kian Meng Lim
- Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore
| | - Lijian Yang
- School of Information Science and Engineering, Shenyang University of Technology, Shenyang, China
| | - Ning Wang
- School of Mechanical Engineering, Shenyang University of Technology, Shenyang, China
| | - Linghui Peng
- School of Mechanical Engineering, Shenyang University of Technology, Shenyang, China
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2
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Sprumont H, Allione F, Schwab F, Wang B, Mucignat C, Lunati I, Scheyer T, Ijspeert A, Jusufi A. Asymmetric fin shape changes swimming dynamics of ancient marine reptiles' soft robophysical models. BIOINSPIRATION & BIOMIMETICS 2024; 19:046005. [PMID: 38626775 DOI: 10.1088/1748-3190/ad3f5e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/16/2024] [Indexed: 05/09/2024]
Abstract
Animals have evolved highly effective locomotion capabilities in terrestrial, aerial, and aquatic environments. Over life's history, mass extinctions have wiped out unique animal species with specialized adaptations, leaving paleontologists to reconstruct their locomotion through fossil analysis. Despite advancements, little is known about how extinct megafauna, such as the Ichthyosauria one of the most successful lineages of marine reptiles, utilized their varied morphologies for swimming. Traditional robotics struggle to mimic extinct locomotion effectively, but the emerging soft robotics field offers a promising alternative to overcome this challenge. This paper aims to bridge this gap by studyingMixosauruslocomotion with soft robotics, combining material modeling and biomechanics in physical experimental validation. Combining a soft body with soft pneumatic actuators, the soft robotic platform described in this study investigates the correlation between asymmetrical fins and buoyancy by recreating the pitch torque generated by extinct swimming animals. We performed a comparative analysis of thrust and torque generated byCarthorhyncus,Utatsusaurus,Mixosaurus,Guizhouichthyosaurus, andOphthalmosaurustail fins in a flow tank. Experimental results suggest that the pitch torque on the torso generated by hypocercal fin shapes such as found in model systems ofGuizhouichthyosaurus,MixosaurusandUtatsusaurusproduce distinct ventral body pitch effects able to mitigate the animal's non-neutral buoyancy. This body pitch control effect is particularly pronounced inGuizhouichthyosaurus, which results suggest would have been able to generate high ventral pitch torque on the torso to compensate for its positive buoyancy. By contrast, homocercal fin shapes may not have been conducive for such buoyancy compensation, leaving torso pitch control to pectoral fins, for example. Across the range of the actuation frequencies of the caudal fins tested, resulted in oscillatory modes arising, which in turn can affect the for-aft thrust generated.
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Affiliation(s)
- Hadrien Sprumont
- Soft Kinetic Group, Engineering Sciences Department, Empa, 8600 Zuerich, Switzerland
- Biorobotics Laboratory, School of Engineering, EPFL, 1015 Lausanne, Switzerland
| | - Federico Allione
- Soft Kinetic Group, Engineering Sciences Department, Empa, 8600 Zuerich, Switzerland
| | - Fabian Schwab
- Soft Kinetic Group, Engineering Sciences Department, Empa, 8600 Zuerich, Switzerland
| | - Bingcheng Wang
- Soft Kinetic Group, Engineering Sciences Department, Empa, 8600 Zuerich, Switzerland
- Institute of Neuroinformatics, University of Zuerich and ETH Zuerich, 8057 Zuerich, Switzerland
| | - Claudio Mucignat
- Laboratory for Computational Engineering, Empa, 8600 Zuerich, Switzerland
| | - Ivan Lunati
- Laboratory for Computational Engineering, Empa, 8600 Zuerich, Switzerland
| | - Torsten Scheyer
- Paläontologisches Institut und Museum, Universität Zürich, 8006 Zuerich, Switzerland
| | - Auke Ijspeert
- Biorobotics Laboratory, School of Engineering, EPFL, 1015 Lausanne, Switzerland
| | - Ardian Jusufi
- Soft Kinetic Group, Engineering Sciences Department, Empa, 8600 Zuerich, Switzerland
- Institute of Neuroinformatics, University of Zuerich and ETH Zuerich, 8057 Zuerich, Switzerland
- Paläontologisches Institut und Museum, Universität Zürich, 8006 Zuerich, Switzerland
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3
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Shafiee M, Bellegarda G, Ijspeert A. Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains. Nat Commun 2024; 15:3073. [PMID: 38594288 DOI: 10.1038/s41467-024-47443-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 03/27/2024] [Indexed: 04/11/2024] Open
Abstract
Quadruped animals are capable of seamless transitions between different gaits. While energy efficiency appears to be one of the reasons for changing gaits, other determinant factors likely play a role too, including terrain properties. In this article, we propose that viability, i.e., the avoidance of falls, represents an important criterion for gait transitions. We investigate the emergence of gait transitions through the interaction between supraspinal drive (brain), the central pattern generator in the spinal cord, the body, and exteroceptive sensing by leveraging deep reinforcement learning and robotics tools. Consistent with quadruped animal data, we show that the walk-trot gait transition for quadruped robots on flat terrain improves both viability and energy efficiency. Furthermore, we investigate the effects of discrete terrain (i.e., crossing successive gaps) on imposing gait transitions, and find the emergence of trot-pronk transitions to avoid non-viable states. Viability is the only improved factor after gait transitions on both flat and discrete gap terrains, suggesting that viability could be a primary and universal objective of gait transitions, while other criteria are secondary objectives and/or a consequence of viability. Moreover, our experiments demonstrate state-of-the-art quadruped robot agility in challenging scenarios.
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Affiliation(s)
- Milad Shafiee
- Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland.
| | - Guillaume Bellegarda
- Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Auke Ijspeert
- Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
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Prakash A, Nair AR, Arunav H, P R R, Akhil VM, Tawk C, Shankar KV. Bioinspiration and biomimetics in marine robotics: a review on current applications and future trends. BIOINSPIRATION & BIOMIMETICS 2024; 19:031002. [PMID: 38467071 DOI: 10.1088/1748-3190/ad3265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 03/11/2024] [Indexed: 03/13/2024]
Abstract
Over the past few years, the research community has witnessed a burgeoning interest in biomimetics, particularly within the marine sector. The study of biomimicry as a revolutionary remedy for numerous commercial and research-based marine businesses has been spurred by the difficulties presented by the harsh maritime environment. Biomimetic marine robots are at the forefront of this innovation by imitating various structures and behaviors of marine life and utilizing the evolutionary advantages and adaptations these marine organisms have developed over millennia to thrive in harsh conditions. This thorough examination explores current developments and research efforts in biomimetic marine robots based on their propulsion mechanisms. By examining these biomimetic designs, the review aims to solve the mysteries buried in the natural world and provide vital information for marine improvements. In addition to illuminating the complexities of these bio-inspired mechanisms, the investigation helps to steer future research directions and possible obstacles, spurring additional advancements in the field of biomimetic marine robotics. Considering the revolutionary potential of using nature's inventiveness to navigate and thrive in one of the most challenging environments on Earth, the current review's conclusion urges a multidisciplinary approach by integrating robotics and biology. The field of biomimetic marine robotics not only represents a paradigm shift in our relationship with the oceans, but it also opens previously unimaginable possibilities for sustainable exploration and use of marine resources by understanding and imitating nature's solutions.
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Affiliation(s)
- Amal Prakash
- Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India
| | - Arjun R Nair
- Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India
| | - H Arunav
- Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India
| | - Rthuraj P R
- Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India
| | - V M Akhil
- School of Interdisciplinary Research, Indian Institute of Technology, Delhi, India
| | - Charbel Tawk
- Department of Industrial and Mechanical Engineering, School of Engineering, Lebanese American University, Byblos, Lebanon
| | - Karthik V Shankar
- Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India
- Centre for Flexible Electronics and Advanced Materials, Amrita Vishwa Vidyapeetham, Amritapuri, India
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Arreguit J, Ramalingasetty ST, Ijspeert A. FARMS: Framework for Animal and Robot Modeling and Simulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.25.559130. [PMID: 38293071 PMCID: PMC10827226 DOI: 10.1101/2023.09.25.559130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The study of animal locomotion and neuromechanical control offers valuable insights for advancing research in neuroscience, biomechanics, and robotics. We have developed FARMS (Framework for Animal and Robot Modeling and Simulation), an open-source, interdisciplinary framework, designed to facilitate access to neuromechanical simulations for modeling, simulation, and analysis of animal locomotion and bio-inspired robotic systems. By providing an accessible and user-friendly platform, FARMS aims to lower the barriers for researchers to explore the complex interactions between the nervous system, musculoskeletal structures, and their environment. Integrating the MuJoCo physics engine in a modular manner, FARMS enables realistic simulations and fosters collaboration among neuroscientists, biologists, and roboticists. FARMS has already been extensively used to study locomotion in animals such as mice, drosophila, fish, salamanders, and centipedes, serving as a platform to investigate the role of central pattern generators and sensory feedback. This article provides an overview of the FARMS framework, discusses its interdisciplinary approach, showcases its versatility through specific case studies, and highlights its effectiveness in advancing our understanding of locomotion. In particular, we show how we used FARMS to study amphibious locomotion by presenting experimental demonstrations across morphologies and environments based on neural controllers with central pattern generators and sensory feedback circuits models. Overall, the goal of FARMS is to contribute to a deeper understanding of animal locomotion, the development of innovative bio-inspired robotic systems, and promote accessibility in neuromechanical research.
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Affiliation(s)
- Jonathan Arreguit
- BioRob, School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Shravan Tata Ramalingasetty
- BioRob, School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, USA
| | - Auke Ijspeert
- BioRob, School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Sándor B, Gros C, Manoonpong P. Editorial: The roles of self-organization and sensory adaptation for locomotion in animals and robots. Front Neurorobot 2024; 18:1372772. [PMID: 38379849 PMCID: PMC10877031 DOI: 10.3389/fnbot.2024.1372772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 01/23/2024] [Indexed: 02/22/2024] Open
Affiliation(s)
- Bulcsú Sándor
- Department of Physics, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Claudius Gros
- Institute for Theoretical Physics, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Poramate Manoonpong
- Bio-inspired Robotics and Neural Engineering Lab, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Rayong, Thailand
- Embodied Artificial Intelligence and Neurorobotics Lab, SDU Biorobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense, Denmark
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7
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Bianchi G, Lanzetti L, Mariana D, Cinquemani S. Bioinspired Design and Experimental Validation of an Aquatic Snake Robot. Biomimetics (Basel) 2024; 9:87. [PMID: 38392132 PMCID: PMC10886812 DOI: 10.3390/biomimetics9020087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 01/26/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
This article presents the design, simulation, and experimental validation of a novel modular aquatic snake robot capable of surface locomotion. The modular structure allows each unit to function independently, facilitating ease of maintenance and adaptability to diverse aquatic environments. Employing the material point method with the moving least squares (MPM-MLS) simulation technique, the robot's dynamic behavior was analyzed, yielding reliable results. The control algorithm, integral to the robot's autonomous navigation, was implemented to enable forward propulsion at high speed, steering, and obstacle detection and avoidance. Extensive testing of the aquatic snake robot was conducted, demonstrating its practical viability. The robot showcased promising swimming capabilities, achieving high speeds and maneuverability. Furthermore, the obstacle detection and avoidance mechanisms were proven effective, showing the robot's ability to navigate through dynamic environments. The presented aquatic snake robot represents an advancement in the field of underwater robotics, offering a modular and versatile solution for tasks ranging from environmental monitoring to search and rescue operations.
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Affiliation(s)
- Giovanni Bianchi
- Dipartimento di Meccanica, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
| | - Luca Lanzetti
- Dipartimento di Meccanica, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
| | - Daniele Mariana
- Dipartimento di Meccanica, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
| | - Simone Cinquemani
- Dipartimento di Meccanica, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
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8
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Saintyves B, Spenko M, Jaeger HM. A self-organizing robotic aggregate using solid and liquid-like collective states. Sci Robot 2024; 9:eadh4130. [PMID: 38266100 DOI: 10.1126/scirobotics.adh4130] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 12/19/2023] [Indexed: 01/26/2024]
Abstract
Designing robotic systems that can change their physical form factor as well as their compliance to adapt to environmental constraints remains a major conceptual and technical challenge. To address this, we introduce the Granulobot, a modular system that blurs the distinction between soft, modular, and swarm robotics. The system consists of gear-like units that each contain a single actuator such that units can self-assemble into larger, granular aggregates using magnetic coupling. These aggregates can reconfigure dynamically and also split into subsystems that might later recombine. Aggregates can self-organize into collective states with solid- and liquid-like properties, thus displaying widely differing compliance. These states can be perturbed locally via actuators or externally via mechanical feedback from the environment to produce adaptive shape-shifting in a decentralized manner. This, in turn, can generate locomotion strategies adapted to different conditions. Aggregates can move over obstacles without using external sensors or coordinates to maintain a steady gait over different surfaces without electronic communication among units. The modular design highlights a physical, morphological form of control that advances the development of resilient robotic systems with the ability to morph and adapt to different functions and conditions.
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Affiliation(s)
| | - Matthew Spenko
- Mechanical, Materials, and Aerospace Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Heinrich M Jaeger
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA
- Department of Physics, University of Chicago, Chicago, IL 60637, USA
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9
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Hu J, Xu Y, Chen P, Xie F, Li H, He K. Design and Reality-Based Modeling Optimization of a Flexible Passive Joint Paddle for Swimming Robots. Biomimetics (Basel) 2024; 9:56. [PMID: 38275453 PMCID: PMC11154456 DOI: 10.3390/biomimetics9010056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024] Open
Abstract
Rowing motion with paired propellers is an essential actuation mechanism for swimming robots. Previous work in this field has typically employed flexible propellers to generate a net thrust or torque by using changes in the compliance values of flexible structures under the influence of a fluid. The low stiffness values of the flexible structures restrict the upper limit of the oscillation frequency and amplitude, resulting in slow swimming speeds. Furthermore, complex coupling between the fluid and the propeller reduce the accuracy of flexible propeller simulations. A design of a flexible passive joint paddle was proposed in this study, and a dynamics model and simulation of the paddle were experimentally verified. In order to optimize the straight swimming speed, a data-driven model was proposed to improve the simulation accuracy. The effects of the joint number and controller parameters on the robot's straight swimming speed were comprehensively investigated. The multi-joint paddle exhibited significantly improved thrust over the single-joint paddle in a symmetric driving mode. The data-driven model reduced the total error of the simulated data of the propulsive force in the range of control parameters to 0.51%. Swimming speed increased by 3.3 times compared to baseline. These findings demonstrate the utility of the proposed dynamics and data-driven models in the multi-objective design of swimming robots.
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Affiliation(s)
- Junzhe Hu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (J.H.); (Y.X.); (H.L.)
- Chongqing University-University of Cincinnati Joint Co-op Institute, Chongqing University, Chongqing 400044, China;
| | - Yaohui Xu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (J.H.); (Y.X.); (H.L.)
| | - Pengyu Chen
- Chongqing University-University of Cincinnati Joint Co-op Institute, Chongqing University, Chongqing 400044, China;
| | - Fengran Xie
- School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China;
| | - Hanlin Li
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (J.H.); (Y.X.); (H.L.)
| | - Kai He
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (J.H.); (Y.X.); (H.L.)
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10
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Wang T, Pierce C, Kojouharov V, Chong B, Diaz K, Lu H, Goldman DI. Mechanical intelligence simplifies control in terrestrial limbless locomotion. Sci Robot 2023; 8:eadi2243. [PMID: 38117866 DOI: 10.1126/scirobotics.adi2243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 11/28/2023] [Indexed: 12/22/2023]
Abstract
Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving "mechanical intelligence"), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans, and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.
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Affiliation(s)
- Tianyu Wang
- Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA 30332, USA
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Dr NW, Atlanta, GA 30318, USA
| | - Christopher Pierce
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr, Atlanta, GA 30332, USA
| | - Velin Kojouharov
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Dr NW, Atlanta, GA 30318, USA
| | - Baxi Chong
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA
| | - Kelimar Diaz
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA
| | - Hang Lu
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr, Atlanta, GA 30332, USA
| | - Daniel I Goldman
- Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA 30332, USA
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA
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11
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Melo K, Horvat T, Ijspeert AJ. Animal robots in the African wilderness: Lessons learned and outlook for field robotics. Sci Robot 2023; 8:eadd8662. [PMID: 38055805 DOI: 10.1126/scirobotics.add8662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 11/10/2023] [Indexed: 12/08/2023]
Abstract
In early 2016, we had the opportunity to test a pair of sprawling posture robots, one designed to mimic a crocodile and another designed to mimic a monitor lizard, along the banks of the Nile River in Uganda, Africa. These robots were developed uniquely for a documentary by the BBC called Spy in the Wild and fell at the intersection of our interests in developing robots to study animals and robots for disaster response and other missions in challenging environments. The documentary required that these robots not only walk and swim in the same harsh, natural environments as the animals that they were modeled on and film up close but also move and even look exactly like the real animals from an aesthetic perspective. This pushed us to take a fundamentally different approach to the design and building of biorobots compared with our typical laboratory-residing robots, in addition to collaborating with sculpting artists to enhance our robots' aesthetics. The robots needed to be designed on the basis of a systematic study of data on the model specimens, be fabricated rapidly, and be reliable and robust enough to handle what the wild would throw at them. Here, we share the research efforts of this collaboration, the design specifications of the robots' hardware and software, the lessons learned from testing these robots in the field first hand, and how the eye-opening experience shaped our subsequent work on disaster response robotics and biorobotics for challenging amphibious scenarios.
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Affiliation(s)
- Kamilo Melo
- KM-RoBoTa Sàrl, Renens, Switzerland
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tomislav Horvat
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Verity AG, Zurich, Switzerland
| | - Auke J Ijspeert
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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12
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Gordleeva SY, Kastalskiy IA, Tsybina YA, Ermolaeva AV, Hramov AE, Kazantsev VB. Control of movement of underwater swimmers: Animals, simulated animates and swimming robots. Phys Life Rev 2023; 47:211-244. [PMID: 38072505 DOI: 10.1016/j.plrev.2023.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 10/29/2023] [Indexed: 12/18/2023]
Abstract
The control of movement in living organisms represents a fundamental task that the brain has evolved to solve. One crucial aspect is how the nervous system organizes the transformation of sensory information into motor commands. These commands lead to muscle activation and subsequent animal movement, which can exhibit complex patterns. One example of such movement is locomotion, which involves the translation of the entire body through space. Central Pattern Generators (CPGs) are neuronal circuits that provide control signals for these movements. Compared to the intricate circuits found in the brain, CPGs can be simplified into networks of neurons that generate rhythmic activation, coordinating muscle movements. Since the 1990s, researchers have developed numerous models of locomotive circuits to simulate different types of animal movement, including walking, flying, and swimming. Initially, the primary goal of these studies was to construct biomimetic robots. However, it became apparent that simplified CPGs alone were not sufficient to replicate the diverse range of adaptive locomotive movements observed in living organisms. Factors such as sensory modulation, higher-level control, and cognitive components related to learning and memory needed to be considered. This necessitated the use of more complex, high-dimensional circuits, as well as novel materials and hardware, in both modeling and robotics. With advancements in high-power computing, artificial intelligence, big data processing, smart materials, and electronics, the possibility of designing a new generation of true bio-mimetic robots has emerged. These robots have the capability to imitate not only simple locomotion but also exhibit adaptive motor behavior and decision-making. This motivation serves as the foundation for the current review, which aims to analyze existing concepts and models of movement control systems. As an illustrative example, we focus on underwater movement and explore the fundamental biological concepts, as well as the mathematical and physical models that underlie locomotion and its various modulations.
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Affiliation(s)
- S Yu Gordleeva
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia
| | - I A Kastalskiy
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia.
| | - Yu A Tsybina
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; I.M. Sechenov First Moscow State Medical University (Sechenov University), 2 Bol'shaya Pirogovskaya St., Moscow, 119435, Russia
| | - A V Ermolaeva
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; I.M. Sechenov First Moscow State Medical University (Sechenov University), 2 Bol'shaya Pirogovskaya St., Moscow, 119435, Russia
| | - A E Hramov
- Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Saint Petersburg State University, 7-9 Universitetskaya Emb., Saint Petersburg, 199034, Russia
| | - V B Kazantsev
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia
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13
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Szorkovszky A, Veenstra F, Glette K. From real-time adaptation to social learning in robot ecosystems. Front Robot AI 2023; 10:1232708. [PMID: 37860631 PMCID: PMC10584317 DOI: 10.3389/frobt.2023.1232708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/18/2023] [Indexed: 10/21/2023] Open
Abstract
While evolutionary robotics can create novel morphologies and controllers that are well-adapted to their environments, learning is still the most efficient way to adapt to changes that occur on shorter time scales. Learning proposals for evolving robots to date have focused on new individuals either learning a controller from scratch, or building on the experience of direct ancestors and/or robots with similar configurations. Here we propose and demonstrate a novel means for social learning of gait patterns, based on sensorimotor synchronization. Using movement patterns of other robots as input can drive nonlinear decentralized controllers such as CPGs into new limit cycles, hence encouraging diversity of movement patterns. Stable autonomous controllers can then be locked in, which we demonstrate using a quasi-Hebbian feedback scheme. We propose that in an ecosystem of robots evolving in a heterogeneous environment, such a scheme may allow for the emergence of generalist task-solvers from a population of specialists.
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Affiliation(s)
- Alex Szorkovszky
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Frank Veenstra
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Kyrre Glette
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
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14
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Wang H, Nonaka T, Abdulali A, Iida F. Coordinating upper limbs for octave playing on the piano via neuro-musculoskeletal modeling. BIOINSPIRATION & BIOMIMETICS 2023; 18:066009. [PMID: 37714178 DOI: 10.1088/1748-3190/acfa51] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 09/15/2023] [Indexed: 09/17/2023]
Abstract
Understanding the coordination of multiple biomechanical degrees of freedom in biological organisms is crucial for unraveling the neurophysiological control of sophisticated motor tasks. This study focuses on the cooperative behavior of upper-limb motor movements in the context of octave playing on the piano. While the vertebrate locomotor system has been extensively investigated, the coherence and precision timing of rhythmic movements in the upper-limb system remain incompletely understood. Inspired by the spinal cord neuronal circuits (central pattern generator, CPG), a computational neuro-musculoskeletal model is proposed to explore the coordination of upper-limb motor movements during octave playing across varying tempos and volumes. The proposed model incorporates a CPG-based nervous system, a physiologically-informed mechanical body, and a piano environment to mimic human joint coordination and expressiveness. The model integrates neural rhythm generation, spinal reflex circuits, and biomechanical muscle dynamics while considering piano playing quality and energy expenditure. Based on real-world human subject experiments, the model has been refined to study tempo transitions and volume control during piano playing. This computational approach offers insights into the neurophysiological basis of upper-limb motor coordination in piano playing and its relation to expressive features.
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Affiliation(s)
- Huijiang Wang
- Bio-Inspired Robotics Lab, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
| | - Tetsushi Nonaka
- Graduate School of Human Development and Environment, Kobe University, Kobe 6578501, Japan
| | - Arsen Abdulali
- Bio-Inspired Robotics Lab, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
| | - Fumiya Iida
- Bio-Inspired Robotics Lab, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
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15
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Ko H, Lauder G, Nagpal R. The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots. J R Soc Interface 2023; 20:20230357. [PMID: 37876271 PMCID: PMC10598440 DOI: 10.1098/rsif.2023.0357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/02/2023] [Indexed: 10/26/2023] Open
Abstract
Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.
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Affiliation(s)
- Hungtang Ko
- Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
| | - George Lauder
- Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Radhika Nagpal
- Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
- Computer Science, Princeton University, Princeton, NJ, USA
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16
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Sánchez-Rodríguez J, Raufaste C, Argentina M. Scaling the tail beat frequency and swimming speed in underwater undulatory swimming. Nat Commun 2023; 14:5569. [PMID: 37689714 PMCID: PMC10492801 DOI: 10.1038/s41467-023-41368-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 09/01/2023] [Indexed: 09/11/2023] Open
Abstract
Undulatory swimming is the predominant form of locomotion in aquatic vertebrates. A myriad of animals of different species and sizes oscillate their bodies to propel themselves in aquatic environments with swimming speed scaling as the product of the animal length by the oscillation frequency. Although frequency tuning is the primary means by which a swimmer selects its speed, there is no consensus on the mechanisms involved. In this article, we propose scaling laws for undulatory swimmers that relate oscillation frequency to length by taking into account both the biological characteristics of the muscles and the interaction of the moving swimmer with its environment. Results are supported by an extensive literature review including approximately 1200 individuals of different species, sizes and swimming environments. We highlight a crossover in size around 0.5-1 m. Below this value, the frequency can be tuned between 2-20 Hz due to biological constraints and the interplay between slow and fast muscles. Above this value, the fluid-swimmer interaction must be taken into account and the frequency is inversely proportional to the length of the animal. This approach predicts a maximum swimming speed around 5-10 m.s-1 for large swimmers, consistent with the threshold to prevent bubble cavitation.
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Affiliation(s)
- Jesús Sánchez-Rodríguez
- Université Côte d'Azur, CNRS, INPHYNI, 17 Rue Julien Lauprêtre, Nice, 06200, France
- Departamento de Física Fundamental, Universidad Nacional de Educación a Distancia, Madrid, 28040, Spain
- Laboratory of Fluid Mechanics and Instabilities, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland
| | - Christophe Raufaste
- Université Côte d'Azur, CNRS, INPHYNI, 17 Rue Julien Lauprêtre, Nice, 06200, France
- Institut Universitaire de France (IUF), 1 Rue Descartes, Paris, 75005, France
| | - Médéric Argentina
- Université Côte d'Azur, CNRS, INPHYNI, 17 Rue Julien Lauprêtre, Nice, 06200, France.
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17
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Katz HR, Hamlet CL. Mechanosensory Feedback in Lamprey Swimming Models and Applications in the Field of Spinal Cord Regeneration. Integr Comp Biol 2023; 63:464-473. [PMID: 37355775 DOI: 10.1093/icb/icad079] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/31/2023] [Accepted: 06/15/2023] [Indexed: 06/26/2023] Open
Abstract
The central pattern generator (CPG) in anguilliform swimming has served as a model for examining the neural basis of locomotion. This system has been particularly valuable for the development of mathematical models. As our biological understanding of the neural basis of locomotion has expanded, so too have these models. Recently, there have been significant advancements in our understanding of the critical role that mechanosensory feedback plays in robust locomotion. This work has led to a push in the field of mathematical modeling to incorporate mechanosensory feedback into CPG models. In this perspective piece, we review advances in the development of these models and discuss how newer complex models can support biological investigation. We highlight lamprey spinal cord regeneration as an area that can both inform these models and benefit from them.
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Affiliation(s)
- Hilary R Katz
- Department of Biology, Western Kentucky University, Bowling Green, KY, 42101, USA
| | - Christina L Hamlet
- Department of Mathematics, Bucknell University, Lewisburg, PA, 17837, USA
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18
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Ijspeert AJ, Daley MA. Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies. J Exp Biol 2023; 226:jeb245784. [PMID: 37565347 DOI: 10.1242/jeb.245784] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has allowed researchers to study the underlying components and some of their interactions across diverse animals. These studies have shown that locomotor neural circuits are distributed in the spinal cord, the midbrain and higher brain regions in vertebrates. The spinal cord plays a key role in locomotor control because it contains central pattern generators (CPGs) - systems of coupled neuronal oscillators that provide coordinated rhythmic control of muscle activation that can be viewed as feedforward controllers - and multiple reflex loops that provide feedback mechanisms. These circuits are activated and modulated by descending pathways from the brain. The relative contributions of CPGs, feedback loops and descending modulation, and how these vary between species and locomotor conditions, remain poorly understood. Robots and neuromechanical simulations can complement experimental approaches by testing specific hypotheses and performing what-if scenarios. This Review will give an overview of key knowledge gained from comparative vertebrate experiments, and insights obtained from neuromechanical simulations and robotic approaches. We suggest that the roles of CPGs, feedback loops and descending modulation vary among animals depending on body size, intrinsic mechanical stability, time required to reach locomotor maturity and speed effects. We also hypothesize that distal joints rely more on feedback control compared with proximal joints. Finally, we highlight important opportunities to address fundamental biological questions through continued collaboration between experimentalists and engineers.
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Affiliation(s)
- Auke J Ijspeert
- BioRobotics Laboratory, EPFL - Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Monica A Daley
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
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19
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Dubuc R, Cabelguen JM, Ryczko D. Locomotor pattern generation and descending control: a historical perspective. J Neurophysiol 2023; 130:401-416. [PMID: 37465884 DOI: 10.1152/jn.00204.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/11/2023] [Accepted: 07/12/2023] [Indexed: 07/20/2023] Open
Abstract
The ability to generate and control locomotor movements depends on complex interactions between many areas of the nervous system, the musculoskeletal system, and the environment. How the nervous system manages to accomplish this task has been the subject of investigation for more than a century. In vertebrates, locomotion is generated by neural networks located in the spinal cord referred to as central pattern generators. Descending inputs from the brain stem initiate, maintain, and stop locomotion as well as control speed and direction. Sensory inputs adapt locomotor programs to the environmental conditions. This review presents a comparative and historical overview of some of the neural mechanisms underlying the control of locomotion in vertebrates. We have put an emphasis on spinal mechanisms and descending control.
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Affiliation(s)
- Réjean Dubuc
- Groupe de Recherche en Activité Physique Adaptée, Département des Sciences de l'Activité Physique, Université du Québec à Montréal, Montreal, Quebec, Canada
- Groupe de Recherche sur le Système Nerveux Central, Département de Neurosciences, Université de Montréal, Montreal, Quebec, Canada
| | - Jean-Marie Cabelguen
- Institut National de la Santé et de la Recherche Médicale (INSERM) U 1215-Neurocentre Magendie, Université de Bordeaux, Bordeaux Cedex, France
| | - Dimitri Ryczko
- Département de Pharmacologie-Physiologie, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Centre de recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
- Neurosciences Sherbrooke, Sherbrooke, Quebec, Canada
- Institut de Pharmacologie de Sherbrooke, Sherbrooke, Quebec, Canada
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20
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Fu Q, Li C. Contact feedback helps snake robots propel against uneven terrain using vertical bending. BIOINSPIRATION & BIOMIMETICS 2023; 18:056002. [PMID: 37433307 DOI: 10.1088/1748-3190/ace672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 07/11/2023] [Indexed: 07/13/2023]
Abstract
Snakes can bend their elongate bodies in various forms to traverse various environments. We understand well how snakes use lateral body bending to push against asperities on flat ground for propulsion, and snake robots can do so effectively. However, snakes can also use vertical bending to push against uneven terrain of large height variation for propulsion, and they can adjust this bending to adapt to novel terrain presumably using mechano-sensing feedback control. Although some snake robots can traverse uneven terrain, few have used vertical bending for propulsion, and how to control this process in novel environments is poorly understood. Here we systematically studied a snake robot with force sensors pushing against large bumps using vertical bending to understand the role of sensory feedback control. We compared a feedforward controller and four feedback controllers that use different sensory information and generate distinct bending patterns and body-terrain interaction. We challenged the robot with increasing backward load and novel terrain geometry that break its contact with the terrain. We further varied how much the feedback control modulated body bending to conform to or push against the terrain to test their effects. Feedforward propagation of vertical bending generated large propulsion when the bending shape matched terrain geometry. However, when perturbations caused loss of contact, the robot easily lost propulsion or had motor overload. Contact feedback control resolved these issues by helping the robot regain contact. Yet excessive conformation interrupted shape propagation and excessive pushing stalled motors frequently. Unlike that using lateral bending, for propulsion generation using vertical bending, body weight that can help maintain contact with the environment but may also overload motors. Our results will help snake robots better traverse uneven terrain with large height variation and can inform how snakes use sensory feedback to control vertical body bending for propulsion.
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Affiliation(s)
- Qiyuan Fu
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America
| | - Chen Li
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America
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21
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Szorkovszky A, Veenstra F, Glette K. Central pattern generators evolved for real-time adaptation to rhythmic stimuli. BIOINSPIRATION & BIOMIMETICS 2023; 18:046020. [PMID: 37339660 DOI: 10.1088/1748-3190/ace017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 06/20/2023] [Indexed: 06/22/2023]
Abstract
For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a control parameter, limiting the adaptability of walking gaits. Here we demonstrate a virtual quadruped robot employing a bio-inspired central pattern generator (CPG) that can spontaneously synchronize its movement to a range of rhythmic stimuli. Multi-objective evolutionary algorithms were used to optimize the variation of movement speed and direction as a function of the brain stem drive and the centre of mass control respectively. This was followed by optimization of an additional layer of neurons that filters fluctuating inputs. As a result, a range of CPGs were able to adjust their gait pattern and/or frequency to match the input period. We show how this can be used to facilitate coordinated movement despite differences in morphology, as well as to learn new movement patterns.
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Affiliation(s)
- Alex Szorkovszky
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Frank Veenstra
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Kyrre Glette
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
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22
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Ramdya P, Ijspeert AJ. The neuromechanics of animal locomotion: From biology to robotics and back. Sci Robot 2023; 8:eadg0279. [PMID: 37256966 DOI: 10.1126/scirobotics.adg0279] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 05/05/2023] [Indexed: 06/02/2023]
Abstract
Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, and robust locomotion can be achieved in autonomous agents. Robotics has already benefitted from neuromechanical principles discovered by investigating animals. These include the use of high-level commands to control low-level central pattern generator-like controllers, which, in turn, are informed by sensory feedback. Reciprocally, neuroscience has benefited from tools and intuitions in robotics to reveal how embodiment, physical interactions with the environment, and sensory feedback help sculpt animal behavior. We illustrate and discuss exemplar studies of this dialog between robotics and neuroscience. We also reveal how the increasing biorealism of simulations and robots is driving these two disciplines together, forging an integrative science of autonomous behavioral control with many exciting future opportunities.
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Affiliation(s)
- Pavan Ramdya
- Neuroengineering Laboratory, Brain Mind Institute and Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Auke Jan Ijspeert
- Biorobotics Laboratory, Institute of Bioengineering, EPFL, Lausanne, Switzerland
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23
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Tamura H, Kamegawa T. Parameter search of a CPG network using a genetic algorithm for a snake robot with tactile sensors moving on a soft floor. Front Robot AI 2023; 10:1138019. [PMID: 37064573 PMCID: PMC10090451 DOI: 10.3389/frobt.2023.1138019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 03/10/2023] [Indexed: 03/31/2023] Open
Abstract
When a snake robot explores a collapsed house as a rescue robot, it needs to move through various obstacles, some of which may be made of soft materials, such as mattresses. In this study, we call mattress-like environment as a soft floor, which deforms when some force is added to it. We focused on the central pattern generator (CPG) network as a control for the snake robot to propel itself on the soft floor and constructed a CPG network that feeds back contact information between the robot and the floor. A genetic algorithm was used to determine the parameters of the CPG network suitable for the soft floor. To verify the obtained parameters, comparative simulations were conducted using the parameters obtained for the soft and hard floor, and the parameters were confirmed to be appropriate for each environment. By observing the difference in snake robot’s propulsion depending on the presence or absence of the tactile sensor feedback signal, we confirmed the effectiveness of the tactile sensor considered in the parameter search.
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24
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Thandiackal R, Lauder G. In-line swimming dynamics revealed by fish interacting with a robotic mechanism. eLife 2023; 12:81392. [PMID: 36744863 PMCID: PMC10032654 DOI: 10.7554/elife.81392] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 02/03/2023] [Indexed: 02/07/2023] Open
Abstract
Schooling in fish is linked to a number of factors such as increased foraging success, predator avoidance, and social interactions. In addition, a prevailing hypothesis is that swimming in groups provides energetic benefits through hydrodynamic interactions. Thrust wakes are frequently occurring flow structures in fish schools as they are shed behind swimming fish. Despite increased flow speeds in these wakes, recent modeling work has suggested that swimming directly in-line behind an individual may lead to increased efficiency. However, only limited data are available on live fish interacting with thrust wakes. Here we designed a controlled experiment in which brook trout, Salvelinus fontinalis, interact with thrust wakes generated by a robotic mechanism that produces a fish-like wake. We show that trout swim in thrust wakes, reduce their tail-beat frequencies, and synchronize with the robotic flapping mechanism. Our flow and pressure field analysis revealed that the trout are interacting with oncoming vortices and that they exhibit reduced pressure drag at the head compared to swimming in isolation. Together, these experiments suggest that trout swim energetically more efficiently in thrust wakes and support the hypothesis that swimming in the wake of one another is an advantageous strategy to save energy in a school.
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25
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Xu P, Zheng J, Liu J, Liu X, Wang X, Wang S, Guan T, Fu X, Xu M, Xie G, Wang ZL. Deep-Learning-Assisted Underwater 3D Tactile Tensegrity. RESEARCH (WASHINGTON, D.C.) 2023; 6:0062. [PMID: 36930813 PMCID: PMC10013964 DOI: 10.34133/research.0062] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 01/09/2023] [Indexed: 01/22/2023]
Abstract
The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals' musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.
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Affiliation(s)
- Peng Xu
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Jiaxi Zheng
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Jianhua Liu
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Xiangyu Liu
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Xinyu Wang
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Siyuan Wang
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Tangzhen Guan
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Xianping Fu
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Minyi Xu
- Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
| | - Guangming Xie
- Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing 100871, China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100871, China.,School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0245, USA
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26
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Ren Z, Shao Y. Future bio-inspired robots require delicate structures. Front Robot AI 2022; 9:1073329. [PMID: 36618011 PMCID: PMC9811312 DOI: 10.3389/frobt.2022.1073329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Ziyu Ren
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany,*Correspondence: Ziyu Ren, ; Yuxiu Shao,
| | - Yuxiu Shao
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure—PSL Research University, Paris, France,*Correspondence: Ziyu Ren, ; Yuxiu Shao,
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27
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Zheng J, Xu P, Meng Z, Liu J, Wang S, Wang X, Xie G, Tao J, Xu M. Design, Fabrication, and Characterization of a Hybrid Bionic Spherical Robotics With Multilegged Feedback Mechanism. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3187514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Jiaxi Zheng
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Peng Xu
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Zhaochen Meng
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Jianhua Liu
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Siyuan Wang
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Xinyu Wang
- Marine Engineering College, Dalian Maritime University, Dalian, China
| | - Guangming Xie
- Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing, China
| | - Jin Tao
- College of Artifical Intelligence, Nankai University, Tianjin, China
| | - Minyi Xu
- Marine Engineering College, Dalian Maritime University, Dalian, China
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28
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Liu W, Duo Y, Liu J, Yuan F, Li L, Li L, Wang G, Chen B, Wang S, Yang H, Liu Y, Mo Y, Wang Y, Fang B, Sun F, Ding X, Zhang C, Wen L. Touchless interactive teaching of soft robots through flexible bimodal sensory interfaces. Nat Commun 2022; 13:5030. [PMID: 36028481 PMCID: PMC9412806 DOI: 10.1038/s41467-022-32702-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 08/12/2022] [Indexed: 11/09/2022] Open
Abstract
In this paper, we propose a multimodal flexible sensory interface for interactively teaching soft robots to perform skilled locomotion using bare human hands. First, we develop a flexible bimodal smart skin (FBSS) based on triboelectric nanogenerator and liquid metal sensing that can perform simultaneous tactile and touchless sensing and distinguish these two modes in real time. With the FBSS, soft robots can react on their own to tactile and touchless stimuli. We then propose a distance control method that enabled humans to teach soft robots movements via bare hand-eye coordination. The results showed that participants can effectively teach a self-reacting soft continuum manipulator complex motions in three-dimensional space through a "shifting sensors and teaching" method within just a few minutes. The soft manipulator can repeat the human-taught motions and replay them at different speeds. Finally, we demonstrate that humans can easily teach the soft manipulator to complete specific tasks such as completing a pen-and-paper maze, taking a throat swab, and crossing a barrier to grasp an object. We envision that this user-friendly, non-programmable teaching method based on flexible multimodal sensory interfaces could broadly expand the domains in which humans interact with and utilize soft robots.
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Affiliation(s)
- Wenbo Liu
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Youning Duo
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Jiaqi Liu
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Feiyang Yuan
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Lei Li
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Luchen Li
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Gang Wang
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Bohan Chen
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Siqi Wang
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Hui Yang
- Institute of Semiconductors, Guangdong Academy of Sciences, Guangdong, 510075, China
| | - Yuchen Liu
- School of General Engineering, Beihang University, Beijing, 100191, China
| | - Yanru Mo
- School of General Engineering, Beihang University, Beijing, 100191, China
| | - Yun Wang
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Bin Fang
- Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Fuchun Sun
- Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Xilun Ding
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China
| | - Chi Zhang
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, China.,School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Li Wen
- School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China.
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29
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Ruppert F, Badri-Spröwitz A. Learning plastic matching of robot dynamics in closed-loop central pattern generators. NAT MACH INTELL 2022. [DOI: 10.1038/s42256-022-00505-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
AbstractAnimals achieve agile locomotion performance with reduced control effort and energy efficiency by leveraging compliance in their muscles and tendons. However, it is not known how biological locomotion controllers learn to leverage the intelligence embodied in their leg mechanics. Here we present a framework to match control patterns and mechanics based on the concept of short-term elasticity and long-term plasticity. Inspired by animals, we design a robot, Morti, with passive elastic legs. The quadruped robot Morti is controlled by a bioinspired closed-loop central pattern generator that is designed to elastically mitigate short-term perturbations using sparse contact feedback. By minimizing the amount of corrective feedback on the long term, Morti learns to match the controller to its mechanics and learns to walk within 1 h. By leveraging the advantages of its mechanics, Morti improves its energy efficiency by 42% without explicit minimization in the cost function.
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30
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Akanyeti O, Di Santo V, Goerig E, Wainwright DK, Liao JC, Castro-Santos T, Lauder GV. Fish-inspired segment models for undulatory steady swimming. BIOINSPIRATION & BIOMIMETICS 2022; 17:046007. [PMID: 35487201 DOI: 10.1088/1748-3190/ac6bd6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 04/29/2022] [Indexed: 06/14/2023]
Abstract
Many aquatic animals swim by undulatory body movements and understanding the diversity of these movements could unlock the potential for designing better underwater robots. Here, we analyzed the steady swimming kinematics of a diverse group of fish species to investigate whether their undulatory movements can be represented using a series of interconnected multi-segment models, and if so, to identify the key factors driving the segment configuration of the models. Our results show that the steady swimming kinematics of fishes can be described successfully using parsimonious models, 83% of which had fewer than five segments. In these models, the anterior segments were significantly longer than the posterior segments, and there was a direct link between segment configuration and swimming kinematics, body shape, and Reynolds number. The models representing eel-like fishes with elongated bodies and fishes swimming at high Reynolds numbers had more segments and less segment length variability along the body than the models representing other fishes. These fishes recruited their anterior bodies to a greater extent, initiating the undulatory wave more anteriorly. Two shape parameters, related to axial and overall body thickness, predicted segment configuration with moderate to high success rate. We found that head morphology was a good predictor of its segment length. While there was a large variation in head segments, the length of tail segments was similar across all models. Given that fishes exhibited variable caudal fin shapes, the consistency of tail segments could be a result of an evolutionary constraint tuned for high propulsive efficiency. The bio-inspired multi-segment models presented in this study highlight the key bending points along the body and can be used to decide on the placement of actuators in fish-inspired robots, to model hydrodynamic forces in theoretical and computational studies, or for predicting muscle activation patterns during swimming.
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Affiliation(s)
- Otar Akanyeti
- Department of Computer Science, Aberystwyth University, Ceredigion, SY23 3FL, United Kingdom
| | - Valentina Di Santo
- Division of Functional Morphology, Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Elsa Goerig
- Museum of Comparative Zoology, Harvard University, Cambridge, MA, United States of America
- S.O. Conte Anadromous Fish Research Center, USGS, Turners Falls, MA, United States of America
| | - Dylan K Wainwright
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, United States of America
| | - James C Liao
- Department of Biology, The Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, FL, United States of America
| | - Theodore Castro-Santos
- S.O. Conte Anadromous Fish Research Center, USGS, Turners Falls, MA, United States of America
| | - George V Lauder
- Museum of Comparative Zoology, Harvard University, Cambridge, MA, United States of America
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31
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Fu Q, Astley HC, Li C. Snakes combine vertical and lateral bending to traverse uneven terrain. BIOINSPIRATION & BIOMIMETICS 2022; 17:036009. [PMID: 35235918 DOI: 10.1088/1748-3190/ac59c5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 03/01/2022] [Indexed: 06/14/2023]
Abstract
Terrestrial locomotion requires generating appropriate ground reaction forces which depend on substrate geometry and physical properties. The richness of positions and orientations of terrain features in the 3D world gives limbless animals like snakes that can bend their body versatility to generate forces from different contact areas for propulsion. Despite many previous studies of how snakes use lateral body bending for propulsion on relatively flat surfaces with lateral contact points, little is known about whether and how much snakes use vertical body bending in combination with lateral bending in 3D terrain. This lack had contributed to snake robots being inferior to animals in stability, efficiency, and versatility when traversing complex 3D environments. Here, to begin to elucidate this, we studied how the generalist corn snake traversed an uneven arena of blocks of random height variation five times its body height. The animal traversed the uneven terrain with perfect stability by propagating 3D bending down its body with little transverse motion (11° slip angle). Although the animal preferred moving through valleys with higher neighboring blocks, it did not prefer lateral bending. Among body-terrain contact regions that potentially provide propulsion, 52% were formed by vertical body bending and 48% by lateral bending. The combination of vertical and lateral bending may dramatically expand the sources of propulsive forces available to limbless locomotors by utilizing various asperities available in 3D terrain. Direct measurements of contact forces are necessary to further understand how snakes coordinate 3D bending along the entire body via sensory feedback to propel through 3D terrain. These studies will open a path to new propulsive mechanisms for snake robots, potentially increasing the performance and versatility in 3D terrain.
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Affiliation(s)
- Qiyuan Fu
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America
| | - Henry C Astley
- Department of Biology, University of Akron, Akron, OH 44325, United States of America
| | - Chen Li
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America
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32
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Hao Z, Zhou W, Gravish N. Proprioceptive feedback design for gait synchronization in collective undulatory robots. Adv Robot 2022. [DOI: 10.1080/01691864.2022.2050810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Zhuonan Hao
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, USA
| | - Wei Zhou
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, USA
| | - Nick Gravish
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, USA
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33
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Course Control of a Manta Robot Based on Amplitude and Phase Differences. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10020285] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Due to external interference, such as waves, the success of underwater missions depends on the turning performance of the vehicle. Manta rays use two broad pectoral fins for propulsion, which provide better anti-interference ability and turning performance. Inspired by biological yaw modes, we use the phase difference between the pectoral fins to realize fast course adjustment and the amplitude difference to realize precise adjustment. We design a bionic robot with pectoral fins and use phase oscillators to realize rhythmic motion. An expected phase difference transition equation is introduced to realize a fast and smooth transition of the output, and the parameters are adjusted online. We combine the phase difference and amplitude difference yaw modes to realize closed-loop course control. Through course interference and adjustment experiments, it is verified that the combined mode is more effective than a single mode. Finally, a rectangular trajectory swimming experiment demonstrates continuous mobility of the robot under the combined mode.
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34
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Li G, Kolomenskiy D, Liu H, Thiria B, Godoy-Diana R. Hydrodynamical Fingerprint of a Neighbour in a Fish Lateral Line. Front Robot AI 2022; 9:825889. [PMID: 35224003 PMCID: PMC8878980 DOI: 10.3389/frobt.2022.825889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/20/2022] [Indexed: 11/13/2022] Open
Abstract
For fish, swimming in group may be favorable to individuals. Several works reported that in a fish school, individuals sense and adjust their relative position to prevent collisions and maintain the group formation. Also, from a hydrodynamic perspective, relative-position and kinematic synchronisation between adjacent fish may considerably influence their swimming performance. Fish may sense the relative-position and tail-beat phase difference with their neighbors using both vision and the lateral-line system, however, when swimming in dark or turbid environments, visual information may become unavailable. To understand how lateral-line sensing can enable fish to judge the relative-position and phase-difference with their neighbors, in this study, based on a verified three-dimensional computational fluid dynamics approach, we simulated two fish swimming adjacently with various configurations. The lateral-line signal was obtained by sampling the surface hydrodynamic stress. The sensed signal was processed by Fast Fourier Transform (FFT), which is robust to turbulence and environmental flow. By examining the lateral-line pressure and shear-stress signals in the frequency domain, various states of the neighboring fish were parametrically identified. Our results reveal that the FFT-processed lateral-line signals in one fish may potentially reflect the relative-position, phase-differences, and the tail-beat frequency of its neighbor. Our results shed light on the fluid dynamical aspects of the lateral-line sensing mechanism used by fish. Furthermore, the presented approach based on FFT is especially suitable for applications in bioinspired swimming robotics. We provide suggestions for the design of artificial systems consisting of multiple stress sensors for robotic fish to improve their performance in collective operation.
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Affiliation(s)
- Gen Li
- Center for Mathematical Science and Advanced Technology, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
- *Correspondence: Gen Li,
| | - Dmitry Kolomenskiy
- Center for Design, Manufacturing and Materials (CDMM), Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Hao Liu
- Graduated School of Engineering, Chiba University, Chiba, Japan
| | - Benjamin Thiria
- Laboratoire de Physique et Mécanique des Milieux Hétérogènes (PMMH), CNRS UMR 7636, ESPCI Paris—PSL University, Sorbonne Université, Université de Paris, Paris, France
| | - Ramiro Godoy-Diana
- Laboratoire de Physique et Mécanique des Milieux Hétérogènes (PMMH), CNRS UMR 7636, ESPCI Paris—PSL University, Sorbonne Université, Université de Paris, Paris, France
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35
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Skandalis DA, Lunsford ET, Liao JC. Corollary discharge enables proprioception from lateral line sensory feedback. PLoS Biol 2021; 19:e3001420. [PMID: 34634044 PMCID: PMC8530527 DOI: 10.1371/journal.pbio.3001420] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 10/21/2021] [Accepted: 09/21/2021] [Indexed: 11/26/2022] Open
Abstract
Animals modulate sensory processing in concert with motor actions. Parallel copies of motor signals, called corollary discharge (CD), prepare the nervous system to process the mixture of externally and self-generated (reafferent) feedback that arises during locomotion. Commonly, CD in the peripheral nervous system cancels reafference to protect sensors and the central nervous system from being fatigued and overwhelmed by self-generated feedback. However, cancellation also limits the feedback that contributes to an animal's awareness of its body position and motion within the environment, the sense of proprioception. We propose that, rather than cancellation, CD to the fish lateral line organ restructures reafference to maximize proprioceptive information content. Fishes' undulatory body motions induce reafferent feedback that can encode the body's instantaneous configuration with respect to fluid flows. We combined experimental and computational analyses of swimming biomechanics and hair cell physiology to develop a neuromechanical model of how fish can track peak body curvature, a key signature of axial undulatory locomotion. Without CD, this computation would be challenged by sensory adaptation, typified by decaying sensitivity and phase distortions with respect to an input stimulus. We find that CD interacts synergistically with sensor polarization to sharpen sensitivity along sensors' preferred axes. The sharpening of sensitivity regulates spiking to a narrow interval coinciding with peak reafferent stimulation, which prevents adaptation and homogenizes the otherwise variable sensor output. Our integrative model reveals a vital role of CD for ensuring precise proprioceptive feedback during undulatory locomotion, which we term external proprioception.
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Affiliation(s)
- Dimitri A. Skandalis
- Department of Biology & Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, Florida, United States of America
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Elias T. Lunsford
- Department of Biology & Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, Florida, United States of America
| | - James C. Liao
- Department of Biology & Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, Florida, United States of America
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36
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Schwab F, Lunsford ET, Hong T, Wiesemüller F, Kovac M, Park YL, Akanyeti O, Liao JC, Jusufi A. Body Caudal Undulation measured by Soft Sensors and emulated by Soft Artificial Muscles. Integr Comp Biol 2021; 61:1955-1965. [PMID: 34415009 PMCID: PMC8699111 DOI: 10.1093/icb/icab182] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/15/2021] [Accepted: 08/18/2021] [Indexed: 11/16/2022] Open
Abstract
We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.
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Affiliation(s)
- Fabian Schwab
- Locomotion in Biorobotic and Somatic Systems Group, Max Planck Institute for Intelligent Systems, Heisenbergstraße 3, 70569, Stuttgart, Germany
| | - Elias T Lunsford
- Department of Biology, Whitney Laboratory for Marine Bioscience, University of Florida, Saint Augustine, Florida, 32080, U.S.A
| | - Taehwa Hong
- Department of Mechanical Engineering, Seoul National University, Seoul, 08826, Korea
| | - Fabian Wiesemüller
- Materials and Technology Center of Robotics, EMPA, Überlandstrasse 129, Zürich, 8600, Switzerland.,Aerial Robotics Lab (ARL), Department of Aeronautics, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Mirko Kovac
- Materials and Technology Center of Robotics, EMPA, Überlandstrasse 129, Zürich, 8600, Switzerland.,Aerial Robotics Lab (ARL), Department of Aeronautics, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Yong-Lae Park
- Department of Mechanical Engineering, Seoul National University, Seoul, 08826, Korea
| | - Otar Akanyeti
- Department of Biology, Whitney Laboratory for Marine Bioscience, University of Florida, Saint Augustine, Florida, 32080, U.S.A.,Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3FL, UK
| | - James C Liao
- Department of Biology, Whitney Laboratory for Marine Bioscience, University of Florida, Saint Augustine, Florida, 32080, U.S.A
| | - Ardian Jusufi
- Locomotion in Biorobotic and Somatic Systems Group, Max Planck Institute for Intelligent Systems, Heisenbergstraße 3, 70569, Stuttgart, Germany
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37
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Tytell ED, Long JH. Biorobotic insights into neuromechanical coordination of undulatory swimming. Sci Robot 2021; 6:6/57/eabk0620. [PMID: 34380758 DOI: 10.1126/scirobotics.abk0620] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 07/23/2021] [Indexed: 11/02/2022]
Abstract
Skin sensors on an eel-like robot couple external hydrodynamic pressure with internal neural patterns for robust swimming.
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Affiliation(s)
- Eric D Tytell
- Department of Biology, Tufts University, Medford, MA 02155, USA.
| | - John H Long
- Departments of Biology and Cognitive Science, Vassar College, Poughkeepsie, NY 12604, USA
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