Abstract
All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta. This robot uses deformations of its body to detect changes in friction force on a substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback.
Highlights
All animals use mechanosensors to help them move in complex and changing environments
We model the mechanical system of a caterpillar as a linear chain of masses linked by real-time tunable springs (RTSs),2 as can be seen in figure 2a
The crawling configurations correspond to Model (i) or Model (ii), in which each segment can receive local sensory information from deformation of the corresponding body part
Summary
All animals use mechanosensors to help them move in complex and changing environments. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta. One approach to addressing this problem is to look at the control mechanisms used by relatively simple and biologically well-known soft animals, whose processes have evolved over millions of years to produce effective locomotion without massively complex brains [17,18] Using this perspective, we have studied a highly tractable animal model, the tobacco hornworm Manduca sexta, and other caterpillar species (figure 1) to understand how animals that lack a hard skeleton can coordinate their motion. Considering their small numbers of neurons and the complexity of their body dynamics, it is conceivable that motion control is achieved through autonomous decentralization in which mechanical interactions and locally distributed signalling organize cohesive movements
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