Multi-gait Locomotion Planning and Tracking for Tendon-actuated Terrestrial Soft Robot (TerreSoRo)

TL;DR

This paper introduces a real-time, closed-loop path planning framework for a tendon-actuated soft robot, TerreSoRo, enabling obstacle navigation through gait synthesis and environment learning, addressing a key challenge in soft robot deployment.

Contribution

It presents the first real-time, closed-loop path planning system for a non-pneumatic soft robot using gait-based planning and environment learning.

Findings

TerreSoRo successfully navigates obstacle-rich environments.

The gait synthesis approach improves adaptability and obstacle avoidance.

Real-time re-planning enables dynamic environment handling.

Abstract

The adaptability of soft robots makes them ideal candidates to maneuver through unstructured environments. However, locomotion challenges arise due to complexities in modeling the body mechanics, actuation, and robot-environment dynamics. These factors contribute to the gap between their potential and actual autonomous field deployment. A closed-loop path planning framework for soft robot locomotion is critical to close the real-world realization gap. This paper presents a generic path planning framework applied to TerreSoRo (Tetra-Limb Terrestrial Soft Robot) with pose feedback. It employs a gait-based, lattice trajectory planner to facilitate navigation in the presence of obstacles. The locomotion gaits are synthesized using a data-driven optimization approach that allows for learning from the environment. The trajectory planner employs a greedy breadth-first search strategy to obtain a collision-free trajectory. The synthesized trajectory is a sequence of rotate-then-translate gait pairs. The control architecture integrates high-level and low-level controllers with real-time localization (using an overhead webcam). TerreSoRo successfully navigates environments with obstacles where path re-planning is performed. To best of our knowledge, this is the first instance of real-time, closed-loop path planning of a non-pneumatic soft robot.