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Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot

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Motion Planning and Iterative Learning Control of a Modular Soft Robotic Snake.

Ming Luo¹, Zhenyu Wan², Yinan Sun²

¹School of Mechanical and Materials Engineering, Washington State University, Pullman, WA, United States.

Frontiers in Robotics and AI

|January 27, 2021

Summary

Researchers developed a soft pneumatic robotic snake with embedded sensors for improved locomotion and obstacle avoidance. This adaptable robot mimics biological snakes, enhancing capabilities for search-and-rescue and confined space inspection tasks.

Keywords:

feedback control motion planning pneumatics snake robot soft robotics

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Area of Science:

Robotics
Soft Robotics
Biomimetic Engineering

Background:

Snake robots offer versatility for inspection, search-and-rescue, and disaster response in complex environments.
Existing snake robots often lack the adaptability and flexibility required for highly constrained or unstructured settings.
Biological snakes provide a model for adaptable locomotion and environmental interaction.

Purpose of the Study:

To introduce a novel soft pneumatic robotic snake with enhanced mobility and environmental adaptability.
To develop and integrate advanced control and motion planning algorithms for autonomous operation.
To demonstrate the robotic snake's capabilities in locomotion and obstacle avoidance.

Main Methods:

Design and fabrication of a modular, pressure-operated soft pneumatic robotic snake.
Integration of customized embedded flexible curvature sensing for proprioceptive feedback.
Implementation of iterative learning control (ILC) for gait correction and adaptive bounding box motion planning for trajectory tracking.
Experimental validation of locomotion and obstacle avoidance maneuvers.

Main Results:

The soft robotic snake demonstrated effective locomotion and gait correction using ILC with curvature sensor feedback.
The adaptive bounding box motion planning algorithm enabled efficient trajectory tracking and obstacle avoidance.
The robotic platform showed high adaptability to the environment due to its soft body design.

Conclusions:

The developed soft pneumatic robotic snake platform, combined with advanced control and planning, paves the way for autonomous soft robotic snake systems.
This research advances the field of soft robotics, offering potential for improved performance in challenging real-world applications.
The integration of sensing, control, and planning in a soft robotic system represents a significant step towards functional autonomy.