Snake-inspired trajectory planning and control for confined pipeline inspection with hyper-redundant manipulators

Abstract

The hyper-redundant manipulator (HRM) can explore narrow and curved pipelines by leveraging its high flexibility and redundancy. However, planning collision-free motion trajectories for HRMs in confined environments remains a significant challenge. To address this issue, a pipeline inspection approach that combines nonlinear model predictive control (NMPC) with the snake-inspired crawling algorithm(SCA) is proposed. The approach consists of three processes: insertion, inspection, and exit. The insertion and exit processes utilize the SCA, inspired by snake motion, to significantly reduce path planning time. The inspection process employs NMPC to generate collision-free motion. The prototype HRM is developed, and inspection experiments are conducted in various complex pipeline scenarios to validate the effectiveness and feasibility of the proposed method. Experimental results demonstrate that the approach effectively minimizes the computational cost of path planning, offering a practical solution for HRM applications in pipeline inspection.