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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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Po T, Kanso E, McHenry MJ. Cooperative transport in sea star locomotion. Curr Biol 2024; 34:2551-2557.e4. [PMID: 38631344 DOI: 10.1016/j.cub.2024.03.042] [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: 11/09/2023] [Revised: 02/14/2024] [Accepted: 03/21/2024] [Indexed: 04/19/2024]
Abstract
It is unclear how animals with radial symmetry control locomotion without a brain. Using a combination of experiments, mathematical modeling, and robotics, we tested the extent to which this control emerges in sea stars (Protoreaster nodosus) from the local control of their hundreds of feet and their mechanical interactions with the body. We discovered that these animals compensate for an experimental increase in their submerged weight by recruiting more feet that synchronize in the power stroke of the locomotor cycle during their bouncing gait. Mathematical modeling of the mechanics of a sea star replicated this response to loading without a central controller. A robotic sea star was found to similarly recruit more actuators under higher loads through purely decentralized control. These results suggest that an array of biological or engineered actuators are capable of cooperative transport where the actuators are dynamically recruited by the mechanics of the body. In particular, the body's vertical oscillations serve to recruit feet in greater numbers to overcome the weight to propel the body forward. This form of distributed control contrasts the conventional view of animal locomotion as governed by the central nervous system and offers inspiration for the design of engineered devices with arrays of actuators.
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Affiliation(s)
- Theodora Po
- Department of Ecology and Evolutionary Biology, University of California, Irvine, 321 Steinhaus Hall, Irvine, CA 92697, USA
| | - Eva Kanso
- Department of Aerospace and Mechanical Engineering, University of Southern California, 854 Downey Way, Los Angeles, CA 90089, USA.
| | - Matthew J McHenry
- Department of Ecology and Evolutionary Biology, University of California, Irvine, 321 Steinhaus Hall, Irvine, CA 92697, USA.
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3
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Li P, Xiong C, Huang B, Sun B, Gong X. Terrestrial locomotion characteristics of climbing perch (Anabas testudineus). J Exp Biol 2024; 227:jeb247238. [PMID: 38752366 DOI: 10.1242/jeb.247238] [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: 12/21/2023] [Accepted: 05/01/2024] [Indexed: 06/07/2024]
Abstract
The evolution and utilization of limbs facilitated terrestrial vertebrate movement on land, but little is known about how other lateral structures enhance terrestrial locomotion in amphibian fishes without terrestrialized limb structures. Climbing perch (Anabas testudineus) exhibit sustained terrestrial locomotion using uniaxial rotating gill covers instead of appendages. To investigate the role of such simple lateral structures in terrestrial locomotion and the motion-generating mechanism of the corresponding locomotor structure configuration (gill covers and body undulation), we measured the terrestrial kinematics of climbing perch and quantitatively analysed its motion characteristics. The digitized locomotor kinematics showed a unique body postural adjustment ability that enables the regulation of the posture of the caudal peduncle for converting lateral bending force into propulsion. An analysis of the coordination characteristics demonstrated that the motion of the gill cover is kinematically independent of axial undulation, suggesting that the gill cover functions as an anchored simple support pole while axial undulation actively mediates body posture and produces propulsive force. The two identified feature shapes explained more than 87% of the complex lateral undulation in multistage locomotion. The kinematic characteristics enhance our understanding of the underlying coordinating mechanism corresponding to locomotor configurations. Our work provides quantitative insight into the terrestrial locomotor adaptation of climbing perch and sheds light on terrestrial motion potential of locomotor configurations containing a typical aquatic body and restricted lateral structure.
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Affiliation(s)
- Peimin Li
- Institute of Medical Equipment Science and Engineering, School of Mechanical Science and Engineering , Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Caihua Xiong
- Institute of Medical Equipment Science and Engineering, School of Mechanical Science and Engineering , Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bo Huang
- Institute of Medical Equipment Science and Engineering, School of Mechanical Science and Engineering , Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Baiyang Sun
- Institute of Medical Equipment Science and Engineering, School of Mechanical Science and Engineering , Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuan Gong
- Institute of Medical Equipment Science and Engineering, School of Mechanical Science and Engineering , Huazhong University of Science and Technology, Wuhan, Hubei, China
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Yao DR, Kim I, Yin S, Gao W. Multimodal Soft Robotic Actuation and Locomotion. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2308829. [PMID: 38305065 DOI: 10.1002/adma.202308829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/02/2024] [Indexed: 02/03/2024]
Abstract
Diverse and adaptable modes of complex motion observed at different scales in living creatures are challenging to reproduce in robotic systems. Achieving dexterous movement in conventional robots can be difficult due to the many limitations of applying rigid materials. Robots based on soft materials are inherently deformable, compliant, adaptable, and adjustable, making soft robotics conducive to creating machines with complicated actuation and motion gaits. This review examines the mechanisms and modalities of actuation deformation in materials that respond to various stimuli. Then, strategies based on composite materials are considered to build toward actuators that combine multiple actuation modes for sophisticated movements. Examples across literature illustrate the development of soft actuators as free-moving, entirely soft-bodied robots with multiple locomotion gaits via careful manipulation of external stimuli. The review further highlights how the application of soft functional materials into robots with rigid components further enhances their locomotive abilities. Finally, taking advantage of the shape-morphing properties of soft materials, reconfigurable soft robots have shown the capacity for adaptive gaits that enable transition across environments with different locomotive modes for optimal efficiency. Overall, soft materials enable varied multimodal motion in actuators and robots, positioning soft robotics to make real-world applications for intricate and challenging tasks.
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Affiliation(s)
- Dickson R Yao
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Inho Kim
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Shukun Yin
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA
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5
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Walas K. Legged robots beyond bioinspiration. Sci Robot 2024; 9:eadp1956. [PMID: 38657089 DOI: 10.1126/scirobotics.adp1956] [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: 03/15/2024] [Accepted: 03/27/2024] [Indexed: 04/26/2024]
Abstract
Advances in engineering enable wheeled-legged hybrid locomotion, an achievement not feasible in biological systems.
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Affiliation(s)
- Krzysztof Walas
- Institute of Robotics and Machine Intelligence, Poznan University of Technology, Poznan, Poland
- IDEAS NCBR, Warsaw, Poland
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6
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Baruzzi V, Lodi M, Storace M. Optimization strategies to obtain smooth gait transitions through biologically plausible central pattern generators. Phys Rev E 2024; 109:014404. [PMID: 38366407 DOI: 10.1103/physreve.109.014404] [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: 07/11/2023] [Accepted: 12/07/2023] [Indexed: 02/18/2024]
Abstract
Central pattern generators are small networks that contribute to generating animal locomotion. The models used to study gait generation and gait transition mechanisms often require biologically accurate neuron and synapse models, with high dimensionality and complex dynamics. Tuning the parameters of these models to elicit network dynamics compatible with gait features is not a trivial task, due to the impossibility of inferring a priori the effects of each parameter on the nonlinear system's emergent dynamics. In this paper we explore the use of global optimization strategies for parameter optimization in multigait central pattern generator (CPG) models with complex cell dynamics and minimal topology. We first consider an existing quadruped CPG model as a test bed for the objective function formulation, then proceed to optimize the parameters of a newly proposed multigait, interlimb hexapod CPG model. We successfully obtain hexapod gaits and prompt gait transitions by varying only control currents, while all CPG parameters, once optimized, are kept fixed. This mechanism of gait transitions is compatible with short-term synaptic plasticity.
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Affiliation(s)
- V Baruzzi
- Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy
| | - M Lodi
- Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy
| | - M Storace
- Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy
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Gilmour KM, Daley MA, Egginton S, Kelber A, McHenry MJ, Patek SN, Sane SP, Schulte PM, Terblanche JS, Wright PA, Franklin CE. Through the looking glass: attempting to predict future opportunities and challenges in experimental biology. J Exp Biol 2023; 226:jeb246921. [PMID: 38059428 DOI: 10.1242/jeb.246921] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
To celebrate its centenary year, Journal of Experimental Biology (JEB) commissioned a collection of articles examining the past, present and future of experimental biology. This Commentary closes the collection by considering the important research opportunities and challenges that await us in the future. We expect that researchers will harness the power of technological advances, such as '-omics' and gene editing, to probe resistance and resilience to environmental change as well as other organismal responses. The capacity to handle large data sets will allow high-resolution data to be collected for individual animals and to understand population, species and community responses. The availability of large data sets will also place greater emphasis on approaches such as modeling and simulations. Finally, the increasing sophistication of biologgers will allow more comprehensive data to be collected for individual animals in the wild. Collectively, these approaches will provide an unprecedented understanding of 'how animals work' as well as keys to safeguarding animals at a time when anthropogenic activities are degrading the natural environment.
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Affiliation(s)
| | - Monica A Daley
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
| | - Stuart Egginton
- School of Biomedical Sciences, University of Leeds, Leeds LS2 9JT, UK
| | - Almut Kelber
- Department of Biology, Lund University, 22362 Lund, Sweden
| | - Matthew J McHenry
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
| | - Sheila N Patek
- Biology Department, Duke University, Durham, NC 27708, USA
| | - Sanjay P Sane
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore, Karnataka 560065, India
| | - Patricia M Schulte
- Department of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - John S Terblanche
- Center for Invasion Biology, Department of Conservation Ecology & Entomology, Stellenbosch University, Stellenbosch 7602, South Africa
| | - Patricia A Wright
- Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Craig E Franklin
- School of the Environment, The University of Queensland, St. Lucia, Brisbane 4072, Australia
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8
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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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9
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Sun X, Hu C, Liu T, Yue S, Peng J, Fu Q. Translating Virtual Prey-Predator Interaction to Real-World Robotic Environments: Enabling Multimodal Sensing and Evolutionary Dynamics. Biomimetics (Basel) 2023; 8:580. [PMID: 38132519 PMCID: PMC10742093 DOI: 10.3390/biomimetics8080580] [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: 09/18/2023] [Revised: 10/18/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Prey-predator interactions play a pivotal role in elucidating the evolution and adaptation of various organism's traits. Numerous approaches have been employed to study the dynamics of prey-predator interaction systems, with agent-based methodologies gaining popularity. However, existing agent-based models are limited in their ability to handle multi-modal interactions, which are believed to be crucial for understanding living organisms. Conversely, prevailing prey-predator integration studies often rely on mathematical models and computer simulations, neglecting real-world constraints and noise. These elusive attributes, challenging to model, can lead to emergent behaviors and embodied intelligence. To bridge these gaps, our study designs and implements a prey-predator interaction scenario that incorporates visual and olfactory sensory cues not only in computer simulations but also in a real multi-robot system. Observed emergent spatial-temporal dynamics demonstrate successful transitioning of investigating prey-predator interactions from virtual simulations to the tangible world. It highlights the potential of multi-robotics approaches for studying prey-predator interactions and lays the groundwork for future investigations involving multi-modal sensory processing while considering real-world constraints.
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Affiliation(s)
- Xuelong Sun
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou 510006, China; (X.S.); (C.H.); (S.Y.)
- School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, China
| | - Cheng Hu
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou 510006, China; (X.S.); (C.H.); (S.Y.)
- School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Tian Liu
- MLTOR Numerical Control Technology Co., Ltd., Zhongshan 528400, China;
| | - Shigang Yue
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou 510006, China; (X.S.); (C.H.); (S.Y.)
- School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Jigen Peng
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou 510006, China; (X.S.); (C.H.); (S.Y.)
- School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, China
| | - Qinbing Fu
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou 510006, China; (X.S.); (C.H.); (S.Y.)
- School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, China
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10
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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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11
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Patanè L, Zhao G. Editorial: Focus on methods: neural algorithms for bio-inspired robotics. Front Neurorobot 2023; 17:1250645. [PMID: 37560410 PMCID: PMC10407788 DOI: 10.3389/fnbot.2023.1250645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 07/17/2023] [Indexed: 08/11/2023] Open
Affiliation(s)
- Luca Patanè
- Department of Engineering, University of Messina, Messina, Italy
| | - Guoping Zhao
- Lauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany
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