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Load Feedback from a Dynamically Scaled Robotic Model of Carausius Morosus Middle Leg

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Biomimetic and Biohybrid Systems (Living Machines 2022)

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Abstract

Load sensing is critical for walking behavior in animals, who have evolved a number of sensory organs and neural systems to improve their agility. In particular, insects measure load on their legs using campaniform sensilla (CS), sensory neurons in the cuticle of high-stress portions of the leg. Extracellular recordings from these sensors in a behaving animal are difficult to collect due to interference from muscle potentials, and some CS groups are largely inaccessible due to their placement on the leg. To better understand what loads the insect leg experiences and what sensory feedback the nervous system may receive during walking, we constructed a dynamically-scaled robotic model of the leg of the stick insect Carausius morosus. We affixed strain gauges in the same positions and orientations as the major CS groups on the leg, i.e., 3, 4, 6A, and 6B. The robotic leg was mounted to a vertically-sliding linear guide and stepped on a treadmill to simulate walking. Data from the strain gauges was run through a dynamic model of CS discharge developed in a previous study. Our experiments reveal stereotypical loading patterns experienced by the leg, even as its weight and joint stiffness is altered. Furthermore, our simulated CS strongly signal the beginning and end of stance phase, two key events in the coordination of walking.

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Acknowledgments

This work was supported by NSF IIS 2113028 as part of the Collaborative Research in Computational Neuroscience Program. A special thanks to Clarissa Goldsmith for providing the necessary experimental data on the MX-28 dynamixel servomotors.

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Correspondence to William P. Zyhowski .

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Zyhowski, W.P., Zill, S.N., Szczecinski, N.S. (2022). Load Feedback from a Dynamically Scaled Robotic Model of Carausius Morosus Middle Leg. In: Hunt, A., et al. Biomimetic and Biohybrid Systems. Living Machines 2022. Lecture Notes in Computer Science(), vol 13548. Springer, Cham. https://doi.org/10.1007/978-3-031-20470-8_14

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  • DOI: https://doi.org/10.1007/978-3-031-20470-8_14

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