A Novel Path Following Method Based on Whole-Body Deviation Evaluation for Hyper-Redundant Robots

Abstract

The accuracy of path following is crucial for collision-free navigation of hyper-redundant robots, especially in narrow environments. However, the existing path following methods only consider the deviations of joints and the end effector, while ignoring the deviations of the robot body. In this letter, a novel path following method is proposed based on whole-body deviation evaluation to achieve high-accuracy path following motion of hyper-redundant robots. Firstly, we introduce a whole-body deviation evaluation algorithm that could precisely quantify the accuracy of path following, which comprehensively considers the deviations of joints, the end effector and linkages along the path. Subsequently, we formulate the path following motion planning as an optimization problem and develop a two-level optimization framework, which reduces the dimensionality of each sub-optimization problem to two. Besides, a refined objective function is proposed to ensure the continuity of the optimized joint angles. Simulations show that the proposed path following method can significantly reduce the path following error by 41.3% and 47.1% for the S-shaped and C-shaped paths, respectively.