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Title: Coordinated crawling via reinforcement learning
Rectilinear crawling locomotion is a primitive and common mode of locomotion in slender soft-bodied animals. It requires coordinated contractions that propagate along a body that interacts frictionally with its environment. We propose a simple approach to understand how this coordination arises in a neuromechanical model of a segmented, soft-bodied crawler via an iterative process that might have both biological antecedents and technological relevance. Using a simple reinforcement learning algorithm, we show that an initial all-to-all neural coupling converges to a simple nearest-neighbour neural wiring that allows the crawler to move forward using a localized wave of contraction that is qualitatively similar to what is observed in Drosophila melanogaster larvae and used in many biomimetic solutions. The resulting solution is a function of how we weight gait regularization in the reward, with a trade-off between speed and robustness to proprioceptive noise. Overall, our results, which embed the brain–body–environment triad in a learning scheme, have relevance for soft robotics while shedding light on the evolution and development of locomotion.  more » « less
Award ID(s):
1922321
PAR ID:
10192210
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Journal of The Royal Society Interface
Volume:
17
Issue:
169
ISSN:
1742-5689
Page Range / eLocation ID:
20200198
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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