Abstract
Wheelless, limbless snake-like robots (Snakebots) feature potential robustness characteristics beyond the capabilities of most wheeled and legged vehicles—ability to traverse terrain that would pose problems for traditional wheeled or legged robots, and insignificant performance degradation when partial damage is inflicted. Some useful features of Snakebots include smaller size of the cross-sectional areas, stability, ability to operate in difficult terrain, good traction, high redundancy, and complete sealing of the internal mechanisms (Dowling in Limbless locomotion: learning to crawl with a snake robot. Doctoral dissertation, Technical Report CMU-RI-TR-97-48. Robotics Institute, Carnegie Mellon University, 1997; Hirose in Biologically inspired robots: snake-like locomotors and manipulators. Oxford University Press, Oxford, 1993). Robots with these properties open up several critical applications in exploration, reconnaissance, medicine and inspection. However, compared to the wheeled and legged vehicles, Snakebots feature (i) more difficult control of locomotion gaits and (ii) inferior speed characteristics. In this work we intend to address the following challenge: how to automatically develop control sequences of Snakebot’s actuators, which allow for achieving the fastest possible speed of locomotion.
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The author thanks Katsunori Shimohara, Thomas Ray and Andrzej Buller for their support of this work.
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Tanev, I. (2013). Learning Mutation Strategies for Evolution and Adaptation of a Simulated Snakebot. In: Prokopenko, M. (eds) Advances in Applied Self-Organizing Systems. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-5113-5_6
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DOI: https://doi.org/10.1007/978-1-4471-5113-5_6
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