Towards Contact-Aided Motion Planning for Tendon-Driven Continuum Robots

Tendon-driven continuum robots (TDCRs), with their flexible backbones, offer the advantage of being used for navigating complex, cluttered environments. However, to do so, they typically require multiple segments, often leadingto complex actuation and control challenges. To this end, we propose a novel approach to navigate cluttered spaces effectively for a single-segment long TDCR which is the simplest topology from a mechanical point of view. Our key insight is that by leveraging contact with the environment we can achieve multiple curvatures without mechanical alterations to the robot. Specifically, we propose a search-based motion planner for a single-segment TDCR. This planner, guided by a specially designed heuristic, discretizes the configuration space and employs a best-first search. The heuristic, crucial for efficient navigation, provides an effective cost-to-go estimation while respecting the kinematic constraints of the TDCR and environmental interactions. We empirically demonstrate the efficiency of our planner—testing over 525 queries in environments with both convex and non-convex obstacles, our planner is demonstrated to have a success rate of about 80% while baselines were not able to obtain a success rate higher than 30%. The difference is attributed to our novel heuristic which is shown to significantly reduce the required search space.

I. Introduction

Tendon-driven continuum robots (TDCRs), bend their flexible backbones via tendon actuation, making them popular for medical and industrial applications for accessing areas with constricted entry-points. As navigating cluttered areas requires more intricate shapes, several segments are typically used, as each segment is capable of bending only in a C-shape. A multi-segment design comes at the price of complex actuation unit design [1] and tendon control. While methods like variable tendon routing [2], layer jamming [3], and locking mechanisms [4] vary curvatures, they demand mechanical modifications to the robot design. In this work we argue that in cluttered environments, we can use a simple single-segment long TDCR that exploits contacts with the environment (contact-aided navigation (CAN)) to achieve variations in curvature.