An Open-Source Snake Hole-Digging Inspired Safety-Critical Insertion Planning and Replanning Framework for Continuum Robots

Abstract

Continuum robots, with their slender, flexible structures, are increasingly utilized for navigating confined spaces via follow-the-leader (FTL) motion to minimize trauma. However, traditional FTL algorithms fail to adjust the entire robot configuration, including the tail, and struggle with navigation in dynamic environments requiring real-time re-planning. We propose a novel FTL motion planning framework inspired by snake hole-digging, enabling optimal shape configuration during insertion. Our approach outperforms the baseline FTL by 75.36% in three environments (circular, confined circular, maze) with six tests. The framework integrates control barrier functions (CBF) and quadratic programming (QP) for real-time obstacle avoidance, with control Lyapunov functions (CLF) ensuring minimal deviation. The target reaching error decreases by 48.43% when using CLF-CBF-QP compared to CBF-QP in four dynamic circular environments with obstacles from different directions. This work, with open-source code, provides a robust solution for continuum robot FTL motion planning in dynamic environments.