Robust Navigation of a Soft Growing Robot by Exploiting Contact with the Environment

TL;DR

This paper introduces a method for soft growing robots to navigate by intentionally exploiting contact with the environment, leading to more robust paths compared to traditional avoidance strategies.

Contribution

It formalizes the interaction model of soft robots with their environment and develops a path planning approach that leverages contact for improved robustness.

Findings

Exploiting contact improves navigation robustness.

The proposed planner outperforms contact-avoidance methods.

Soft robots can safely use environmental contact for navigation.

Abstract

Navigation and motion control of a robot to a destination are tasks that have historically been performed with the assumption that contact with the environment is harmful. This makes sense for rigid-bodied robots where obstacle collisions are fundamentally dangerous. However, because many soft robots have bodies that are low-inertia and compliant, obstacle contact is inherently safe. As a result, constraining paths of the robot to not interact with the environment is not necessary and may be limiting. In this paper, we mathematically formalize interactions of a soft growing robot with a planar environment in an empirical kinematic model. Using this interaction model, we develop a method to plan paths for the robot to a destination. Rather than avoiding contact with the environment, the planner exploits obstacle contact when beneficial for navigation. We find that a planner that takes into account and capitalizes on environmental contact produces paths that are more robust to uncertainty than a planner that avoids all obstacle contact.