Tip-following Path Planning and Its Performance Analysis for Hyper-redundant Manipulators

Abstract

The hyper-redundant manipulators have the features of large length/diameter ratio, high degree of freedoms and good dexterity. To improve the efficiency of their motion in confined space, a tip-following path planning algorithm is proposed. With the feed motion of the base, the manipulators' links and joints can track a desired path curve, sweeping through a tiny area in a 3D confined space. To enhance the efficiency of the algorithm, an iteratively sequential searching method is proposed for the fast matching between the manipulators' key-points and the path curve. A linear interpolation optimization method is then developed to reduce the path following errors caused by discretization of the path curve. The performance of the algorithm is evaluated in terms of the position accuracy, movement smoothness and calculation efficiency based on the simulation of a hyper-redundant manipulator with 12 joints. The results show that the manipulator accurately follows the desired path with deviations of less than 5 μm, and the average computation time is about 1 ms. The algorithm is suitable for spatial motions and is effective to satisfy the requirements of the real-time control.