Gait control in a soft robot by sensing interactions with the environment using self-deformation.

Area of Science:

• Robotics
• Biomimetics
• Locomotion

Background:

• Animals utilize mechanosensors in soft tissues for movement in dynamic environments.
• Sensory feedback arises from tissue deformation during interaction with the environment.
• Mechanical responses of tissues during movement contain valuable environmental information.

Purpose of the Study:

• To explore how sensory information from tissue deformation can control movement.
• To develop a soft-bodied crawling robot inspired by the tobacco hornworm (Manduca sexta).
• To investigate decentralized control strategies for soft robot locomotion.

Main Methods:

• Developed a soft robot using body deformations to detect substrate friction.
• Implemented local sensory feedback for coupled oscillators controlling locomotion.
• Validated the control strategy through simulation and experiments with a 3D-printed soft robot.

Main Results:

• Simple oscillators generated propagating waves and inching locomotion via decentralized control.
• Body part deformations enabled fully decentralized crawling.
• Gait patterns were shown to switch based on surface contact points, confirmed numerically and experimentally.

Conclusions:

• The findings aid in designing adaptable and robust locomotion control systems for soft robots.
• The study suggests testable hypotheses for how soft-bodied animals use sensory feedback for movement.
• Decentralized control based on mechanosensation offers a promising approach for bio-inspired robotics.