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Mangan M, Floreano D, Yasui K, Trimmer BA, Gravish N, Hauert S, Webb B, Manoonpong P, Szczecinski N. A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research. BIOINSPIRATION & BIOMIMETICS 2023; 18:035005. [PMID: 36881919 DOI: 10.1088/1748-3190/acc223] [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: 07/19/2022] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.
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Affiliation(s)
- Michael Mangan
- The University of Sheffield, Mappin St, Sheffield S10 2TN, United Kingdom
| | - Dario Floreano
- Ecole Polytechnique Federale de Lausanne, Laboratory of Intelligent Systems, Station 9, Lausanne CH-1015, Switzerland
| | - Kotaro Yasui
- Tohoku University, Frontier Research Institute for Interdisciplinary Sciences, 6-3 Aramaki aza Aoba, Aoba-ku, Sendai 980-8578, Japan
| | - Barry A Trimmer
- Tufts University, Biology, 200 Boston Av, Boston, MA 02111, United States of America
| | - Nick Gravish
- University of California San Diego, Mechanical and Aerospace Engineering, Building EBU II, La Jolla, CA 92093, United States of America
| | - Sabine Hauert
- University of Bristol, Engineering Mathematics, Bristol BS8 1QU, United Kingdom
| | - Barbara Webb
- University of Edinburgh, School of Informatics, 10 Crichton St, Edinburgh EH8 9AB, United Kingdom
| | - Poramate Manoonpong
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, People's Republic of China
- Bio-Inspired Robotics and Neural Engineering Laboratory, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Wangchan Valley, Rayong 21210, Thailand
| | - Nicholas Szczecinski
- West Virginia University, Mechanical and Aerospace Engineering, Morgantown, WV 26506-6201, United States of America
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Zyhowski WP, Zill SN, Szczecinski NS. Adaptive load feedback robustly signals force dynamics in robotic model of Carausius morosus stepping. Front Neurorobot 2023; 17:1125171. [PMID: 36776993 PMCID: PMC9908954 DOI: 10.3389/fnbot.2023.1125171] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 01/10/2023] [Indexed: 01/27/2023] Open
Abstract
Animals utilize a number of neuronal systems to produce locomotion. One type of sensory organ that contributes in insects is the campaniform sensillum (CS) that measures the load on their legs. Groups of the receptors are found on high stress regions of the leg exoskeleton and they have significant effects in adapting walking behavior. Recording from these sensors in freely moving animals is limited by technical constraints. To better understand the load feedback signaled by CS to the nervous system, we have constructed a dynamically scaled robotic model of the Carausius morosus stick insect middle leg. The leg steps on a treadmill and supports weight during stance to simulate body weight. Strain gauges were mounted in the same positions and orientations as four key CS groups (Groups 3, 4, 6B, and 6A). Continuous data from the strain gauges were processed through a previously published dynamic computational model of CS discharge. Our experiments suggest that under different stepping conditions (e.g., changing "body" weight, phasic load stimuli, slipping foot), the CS sensory discharge robustly signals increases in force, such as at the beginning of stance, and decreases in force, such as at the end of stance or when the foot slips. Such signals would be crucial for an insect or robot to maintain intra- and inter-leg coordination while walking over extreme terrain.
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Affiliation(s)
- William P. Zyhowski
- Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, United States,*Correspondence: William P. Zyhowski,
| | - Sasha N. Zill
- Department of Biomedical Sciences, Marshall University, Huntington, WV, United States
| | - Nicholas S. Szczecinski
- Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, United States
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Webster-Wood VA, Guix M, Xu NW, Behkam B, Sato H, Sarkar D, Sanchez S, Shimizu M, Parker KK. Biohybrid robots: recent progress, challenges, and perspectives. BIOINSPIRATION & BIOMIMETICS 2022; 18:015001. [PMID: 36265472 DOI: 10.1088/1748-3190/ac9c3b] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.
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Affiliation(s)
- Victoria A Webster-Wood
- Mechanical Engineering, Biomedical Engineering (by courtesy), McGowan Institute of Regenerative Medicine, Carnegie Mellon University, Pittsburgh, PA 15116, United States of America
| | - Maria Guix
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Baldiri-Reixac 10-12, 08028 Barcelona, Spain
- Departament de Ciència dels Materials i Química Física, Institut de Química Teòrica i Computacional Barcelona, Universitat de Barcelona, 08028 Barcelona, Spain
| | - Nicole W Xu
- Laboratories for Computational Physics and Fluid Dynamics, U.S. Naval Research Laboratory, Code 6041, Washington, DC, United States of America
| | - Bahareh Behkam
- Department of Mechanical Engineering, Institute for Critical Technology and Applied Science, Blacksburg, VA 24061, United States of America
| | - Hirotaka Sato
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 65 Nanyang Drive, Singapore, 637460, Singapore
| | - Deblina Sarkar
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
| | - Samuel Sanchez
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Baldiri-Reixac 10-12, 08028 Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Avda. Lluis Companys 23, 08010 Barcelona, Spain
| | - Masahiro Shimizu
- Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-machi, Toyonaka, Osaka, Japan
| | - Kevin Kit Parker
- Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States of America
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Manoonpong P, Patanè L, Xiong X, Brodoline I, Dupeyroux J, Viollet S, Arena P, Serres JR. Insect-Inspired Robots: Bridging Biological and Artificial Systems. SENSORS (BASEL, SWITZERLAND) 2021; 21:7609. [PMID: 34833685 PMCID: PMC8623770 DOI: 10.3390/s21227609] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 12/18/2022]
Abstract
This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.
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Affiliation(s)
- Poramate Manoonpong
- Embodied Artificial Intelligence and Neurorobotics Laboratory, SDU Biorobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odense, Denmark;
- Bio-Inspired Robotics and Neural Engineering Laboratory, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Rayong 21210, Thailand
| | - Luca Patanè
- Department of Engineering, University of Messina, 98100 Messina, Italy
| | - Xiaofeng Xiong
- Embodied Artificial Intelligence and Neurorobotics Laboratory, SDU Biorobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odense, Denmark;
| | - Ilya Brodoline
- Department of Biorobotics, Aix Marseille University, CNRS, ISM, CEDEX 07, 13284 Marseille, France; (I.B.); (S.V.)
| | - Julien Dupeyroux
- Faculty of Aerospace Engineering, Delft University of Technology, 52600 Delft, The Netherlands;
| | - Stéphane Viollet
- Department of Biorobotics, Aix Marseille University, CNRS, ISM, CEDEX 07, 13284 Marseille, France; (I.B.); (S.V.)
| | - Paolo Arena
- Department of Electrical, Electronic and Computer Engineering, University of Catania, 95131 Catania, Italy
| | - Julien R. Serres
- Department of Biorobotics, Aix Marseille University, CNRS, ISM, CEDEX 07, 13284 Marseille, France; (I.B.); (S.V.)
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5
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Goldsmith CA, Quinn RD, Szczecinski NS. Investigating the role of low level reinforcement reflex loops in insect locomotion. BIOINSPIRATION & BIOMIMETICS 2021; 16:065008. [PMID: 34547724 DOI: 10.1088/1748-3190/ac28ea] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/21/2021] [Indexed: 06/13/2023]
Abstract
Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the 'lower level' ventral nerve cord (VNC) and the 'higher level' head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as 'positive feedback' may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the 'reflex reversal' of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect (Carausius morosus) femur-tibia (FTi) and coxa-trochanter joint control networks 'in-the-loop' with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce 'sideways stepping'. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network's flexion position and velocity afferents generated a reflex reversal in the robot limb's FTi joint. We also explored the intact network's ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control.
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Affiliation(s)
- C A Goldsmith
- West Virginia University, One Waterfront Place, Morgantown, WV 26506, United States of America
| | - R D Quinn
- Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States of America
| | - N S Szczecinski
- West Virginia University, One Waterfront Place, Morgantown, WV 26506, United States of America
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Szczecinski NS, Dallmann CJ, Quinn RD, Zill SN. A computational model of insect campaniform sensilla predicts encoding of forces during walking. BIOINSPIRATION & BIOMIMETICS 2021; 16:065001. [PMID: 34384067 DOI: 10.1088/1748-3190/ac1ced] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/12/2021] [Indexed: 06/13/2023]
Abstract
Control of forces is essential in both animals and walking machines. Insects measure forces as strains in their exoskeletons via campaniform sensilla (CS). Deformations of cuticular caps embedded in the exoskeleton excite afferents that project to the central nervous system. CS afferent firing frequency (i.e. 'discharge') is highly dynamic, correlating with the rate of change of the force. Discharges adapt over time to tonic forces and exhibit hysteresis during cyclic loading.In this study we characterized a phenomenological model that predicts CS discharge, in which discharge is proportional to the instantaneous stimulus force relative to an adaptive variable. In contrast to previous studies of sensory adaptation, our model (1) is nonlinear and (2) reproduces the characteristic power-law adaptation with first order dynamics only (i.e. no 'fractional derivatives' are required to explain dynamics). We solve the response of the system analytically in multiple cases and use these solutions to derive the dynamics of the adaptive variable. We show that the model can reproduce responses of insect CS to many different force stimuli after being tuned to reproduce only one response, suggesting that the model captures the underlying dynamics of the system. We show that adaptation to tonic forces, rate-sensitivity, and hysteresis are different manifestations of the same underlying mechanism: the adaptive variable. We tune the model to replicate the dynamics of three different CS groups from two insects (cockroach and stick insect), demonstrating that it is generalizable. We also invert the model to estimate the stimulus force given the discharge recording from the animal. We discuss the adaptive neural and mechanical processes that the model may mimic and the model's use for understanding the role of load feedback in insect motor control. A preliminary model and results were previously published in the proceedings of the Conference on Biohybrid and Biomimetic Systems.
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Affiliation(s)
- Nicholas S Szczecinski
- Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV 26505, United States of America
| | - Chris J Dallmann
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, United States of America
| | - Roger D Quinn
- Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, United States of America
| | - Sasha N Zill
- Department of Biomedical Sciences, Joan C Edwards School of Medicine, Marshall University, Huntington, WV 25755, United States of America
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Taylor BK, Lohmann KJ, Havens LT, Lohmann CMF, Granger J. Long-distance transequatorial navigation using sequential measurements of magnetic inclination angle. J R Soc Interface 2021; 18:20200887. [PMID: 33402018 PMCID: PMC7879752 DOI: 10.1098/rsif.2020.0887] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 12/03/2020] [Indexed: 11/12/2022] Open
Abstract
Diverse taxa use Earth's magnetic field in combination with other sensory modalities to accomplish navigation tasks ranging from local homing to long-distance migration across continents and ocean basins. Several animals have the ability to use the inclination or tilt of magnetic field lines as a component of a magnetic compass sense that can be used to maintain migratory headings. In addition, a few animals are able to distinguish among different inclination angles and, in effect, exploit inclination as a surrogate for latitude. Little is known, however, about the role that magnetic inclination plays in guiding long-distance migrations. In this paper, we use an agent-based modelling approach to investigate whether an artificial agent can successfully execute a series of transequatorial migrations by using sequential measurements of magnetic inclination. The agent was tested with multiple navigation strategies in both present-day and reversed magnetic fields. The findings (i) demonstrate that sequential inclination measurements can enable migrations between the northern and southern hemispheres, and (ii) demonstrate that an inclination-based strategy can tolerate a reversed magnetic field, which could be useful in the development of autonomous engineered systems that must be robust to magnetic field changes. The findings also appear to be consistent with the results of some animal navigation experiments, although whether any animal exploits a strategy of using sequential measurements of inclination remains unknown.
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Affiliation(s)
- Brian K. Taylor
- Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kenneth J. Lohmann
- Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Luke T. Havens
- Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Catherine M. F. Lohmann
- Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jesse Granger
- Department of Biology, Duke University, Durham, NC, USA
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Goldsmith CA, Szczecinski NS, Quinn RD. Neurodynamic modeling of the fruit fly Drosophila melanogaster. BIOINSPIRATION & BIOMIMETICS 2020; 15:065003. [PMID: 32924978 DOI: 10.1088/1748-3190/ab9e52] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers modeled after the anatomy and function of the insect nervous system. As such, Drosophibot has been designed to capture features of the animal's biomechanics in order to better test the neural controllers. These features include: dynamically scaling the robot to match the fruit fly by designing its joint elasticity and movement speed; a biomimetic actuator control scheme that converts neural activity into motion in the same way as observed in insects; biomimetic sensing, including proprioception from all leg joints and strain sensing from all leg segments; and passively compliant tarsi that mimic the animal's passive compliance to the walking substrate. We incorporated these features into a dynamical simulation of Drosophibot, and demonstrate that its actuators and sensors perform in an animal-like way. We used this simulation to test a neural walking controller based on anatomical and behavioral data from insects. Finally, we describe Drosophibot's hardware and show that the animal-like features of the simulation transfer to the physical robot.
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Affiliation(s)
- C A Goldsmith
- Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States of America
| | - N S Szczecinski
- Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States of America
| | - R D Quinn
- Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States of America
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9
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Affiliation(s)
- Barbara Webb
- School of Informatics, University of Edinburgh, Edinburgh, UK
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10
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Modeling the Dynamic Sensory Discharges of Insect Campaniform Sensilla. BIOMIMETIC AND BIOHYBRID SYSTEMS 2020. [DOI: 10.1007/978-3-030-64313-3_33] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
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11
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Taylor BK, Corbin S. Bioinspired magnetoreception and navigation in nonorthogonal environments using magnetic signatures. BIOINSPIRATION & BIOMIMETICS 2019; 14:066009. [PMID: 31480024 DOI: 10.1088/1748-3190/ab40f8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Diverse taxa use Earth's magnetic field in conjunction with other sensory modalities to accomplish navigation tasks ranging from local homing to long-distance migration across continents and ocean basins. However, despite extensive research, the mechanisms that underlie animal magnetoreception are not clearly understood, and how animals use Earth's magnetic field to navigate is an active area of investigation. Concurrently, Earth's magnetic field offers a signal that engineered systems can leverage for navigation in environments where man-made systems such as GPS are unavailable or unreliable. Using a proxy for Earth's magnetic field, and inspired by migratory animal behavior, this work implements a behavioral strategy that uses combinations of magnetic field inclination and intensity as rare or unique signatures that mark specific locations. Specifically, to increase the realism of previous work, in this study, a simulated agent uses a magnetic signatures based strategy to migrate in magnetic environments where lines of constant inclination and intensity are not necessarily orthogonal. The results further support existing notions that some animals may use combinations of magnetic properties as navigational markers, and provide insights into features and constraints that could enable navigational success or failure in either a biological or engineered system.
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Affiliation(s)
- Brian K Taylor
- Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America. Author to whom correspondence should be addressed
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12
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Tinker KA, Ottesen EA. The hindgut microbiota of praying mantids is highly variable and includes both prey-associated and host-specific microbes. PLoS One 2018; 13:e0208917. [PMID: 30533025 PMCID: PMC6289422 DOI: 10.1371/journal.pone.0208917] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 11/26/2018] [Indexed: 01/08/2023] Open
Abstract
Praying mantids are predators that consume a wide variety of insects. While the gut microbiome of carnivorous mammals is distinct from that of omnivores and herbivores, the role of the gut microbiome among predatory insects is relatively understudied. Praying mantids are the closest known relatives to termites and cockroaches, which are known for their diverse gut microbiota. However, little is known about the mantid gut microbiota or their importance to host health. In this work, we report the results of a 16S rRNA gene-based study of gut microbiome composition in adults and late-instar larvae of three mantid species. We found that the praying mantis gut microbiome exhibits substantial variation in bacterial diversity and community composition. The hindgut of praying mantids were often dominated by microbes that are present in low abundance or not found in the guts of their insect prey. Future studies will explore the role of these microbes in the digestion of the dietary substrates and/or the degradation of toxins produced by their insect prey.
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Affiliation(s)
- Kara A. Tinker
- Department of Microbiology, University of Georgia, Athens, Georgia, United States of America
| | - Elizabeth A. Ottesen
- Department of Microbiology, University of Georgia, Athens, Georgia, United States of America
- * E-mail:
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13
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Taylor BK. Bioinspired magnetoreception and navigation using magnetic signatures as waypoints. BIOINSPIRATION & BIOMIMETICS 2018; 13:046003. [PMID: 29763413 DOI: 10.1088/1748-3190/aabbec] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Diverse taxa use Earth's magnetic field in conjunction with other sensory modalities to accomplish navigation tasks ranging from local homing to long-distance migration across continents and ocean basins. However, despite extensive research, the mechanisms that underlie animal magnetoreception are not clearly understood, and how animals use Earth's magnetic field to navigate is an active area of investigation. Concurrently, Earth's magnetic field offers a signal that engineered systems can leverage for navigation in environments where man-made systems such as GPS are unavailable or unreliable. Using a proxy for Earth's magnetic field, and inspired by migratory animal behavior, this work implements a behavioral strategy that uses combinations of magnetic field properties as rare or unique signatures that mark specific locations. Using a discrete number of these signatures as goal waypoints, the strategy navigates through a closed set of points several times in a variety of environmental conditions, and with various levels of sensor noise. The results from this engineering/quantitative biology approach support existing notions that some animals may use combinations of magnetic properties as navigational markers, and provides insights into features and constraints that would enable navigational success or failure. The findings also offer insights into how autonomous engineered platforms might be designed to leverage the magnetic field as a navigational resource.
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Affiliation(s)
- Brian K Taylor
- Integrated Sensing and Processing Sciences, Air Force Research Laboratory-Munitions Directorate, Eglin Air Force Base, FL 32542, United States of America
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Szczecinski NS, Quinn RD. Leg-local neural mechanisms for searching and learning enhance robotic locomotion. BIOLOGICAL CYBERNETICS 2018; 112:99-112. [PMID: 28782078 DOI: 10.1007/s00422-017-0726-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 07/30/2017] [Indexed: 06/07/2023]
Abstract
Adapting motor output based on environmental forces is critical for successful locomotion in the real world. Arthropods use at least two neural mechanisms to adjust muscle activation while walking based on detected forces. Mechanism 1 uses negative feedback of leg depressor force to ensure that each stance leg supports an appropriate amount of the body's weight. Mechanism 2 encourages searching for ground contact if the leg supports no body weight. We expand the neural controller for MantisBot, a robot based upon a praying mantis, to include these mechanisms by incorporating leg-local memory and command neurons, as observed in arthropods. We present results from MantisBot transitioning between searching and stepping, mimicking data from animals as reported in the literature.
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Abstract
The purpose of this work is to better understand how animals control locomotion. This knowledge can then be applied to neuromechanical design to produce more capable and adaptable robot locomotion. To test hypotheses about animal motor control, we model animals and their nervous systems with dynamical simulations, which we call synthetic nervous systems (SNS). However, one major challenge is picking parameter values that produce the intended dynamics. This paper presents a design process that solves this problem without the need for global optimization. We test this method by selecting parameter values for SimRoach2, a dynamical model of a cockroach. Each leg joint is actuated by an antagonistic pair of Hill muscles. A distributed SNS was designed based on pathways known to exist in insects, as well as hypothetical pathways that produced insect-like motion. Each joint’s controller was designed to function as a proportional-integral (PI) feedback loop and tuned with numerical optimization. Once tuned, SimRoach2 walks through a simulated environment, with several cockroach-like features. A model with such reliable low-level performance is necessary to investigate more sophisticated locomotion patterns in the future.
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Szczecinski NS, Hunt AJ, Quinn RD. A Functional Subnetwork Approach to Designing Synthetic Nervous Systems That Control Legged Robot Locomotion. Front Neurorobot 2017; 11:37. [PMID: 28848419 PMCID: PMC5552699 DOI: 10.3389/fnbot.2017.00037] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Accepted: 07/17/2017] [Indexed: 11/13/2022] Open
Abstract
A dynamical model of an animal's nervous system, or synthetic nervous system (SNS), is a potentially transformational control method. Due to increasingly detailed data on the connectivity and dynamics of both mammalian and insect nervous systems, controlling a legged robot with an SNS is largely a problem of parameter tuning. Our approach to this problem is to design functional subnetworks that perform specific operations, and then assemble them into larger models of the nervous system. In this paper, we present networks that perform addition, subtraction, multiplication, division, differentiation, and integration of incoming signals. Parameters are set within each subnetwork to produce the desired output by utilizing the operating range of neural activity, R, the gain of the operation, k, and bounds based on biological values. The assembly of large networks from functional subnetworks underpins our recent results with MantisBot.
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Affiliation(s)
- Nicholas S Szczecinski
- Biologically Inspired Robotics Laboratory, Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Alexander J Hunt
- Department of Mechanical and Materials Engineering, Portland State University, Portland, OR, United States
| | - Roger D Quinn
- Biologically Inspired Robotics Laboratory, Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH, United States
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Aoi S, Manoonpong P, Ambe Y, Matsuno F, Wörgötter F. Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review. Front Neurorobot 2017; 11:39. [PMID: 28878645 PMCID: PMC5572352 DOI: 10.3389/fnbot.2017.00039] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Accepted: 07/31/2017] [Indexed: 12/02/2022] Open
Abstract
Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots.
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Affiliation(s)
- Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto UniversityKyoto, Japan
| | - Poramate Manoonpong
- Embodied AI & Neurorobotics Lab, Centre for Biorobotics, Mærsk Mc-Kinney Møller Institute, University of Southern DenmarkOdense, Denmark
| | - Yuichi Ambe
- Department of Applied Information Sciences, Graduate School of Information Sciences, Tohoku UniversityAoba-ku, Japan
| | - Fumitoshi Matsuno
- Department of Mechanical Engineering and Science, Graduate School of Engineering, Kyoto UniversityKyoto, Japan
| | - Florentin Wörgötter
- Bernstein Center for Computational Neuroscience, Third Institute of Physics, Georg-August-Universität GöttingenGöttingen, Germany
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Reeve MA. MantisBot successfully mimics prey tracking. J Exp Biol 2017. [DOI: 10.1242/jeb.147462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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