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

arXiv: https://arxiv.org/abs/1908.08645 · HTML: https://mlsanity.com/paper/1908.08645/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Aug 2019.

## Built on by (most cited first, 2 of 2)

- [FishFormer: Annulus Slicing-based Transformer for Fisheye Rectification with Efficacy Domain Exploration](https://mlsanity.com/paper/2207.01925/) (2022)
- [Contact-Aided Navigation of Flexible Robotic Endoscope Using Deep Reinforcement Learning in Dynamic Stomach](https://mlsanity.com/paper/2509.00319/) (2025)

## Abstract (arXiv)

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.