Multi-objective Trajectory Optimization of Redundant Manipulator for Patient Assistance

Abstract

A trajectory planning algorithm of a seven-degree-of-freedom manipulator based on a high-order non-uniform rational B-spline curve(NURBS) is described in this paper. Based on inverse kinematics analysis of the manipulator, multi-objective optimization is carried out in terms of overall time consumption, energy consumption, and motion stability. Firstly, the high-order continuous curve with specified endpoints is planned according to the trajectory interpolation of the quintic NURBS curve. For the optimization objective, the corresponding three optimization functions are time function, acceleration function, and acceleration rate function, and the multiple sub-population non-dominated sorting genetic algorithm III (NSGA-III) is used for multi-objective optimization. The Pareto optimal surface of the NURBS curve is obtained by this algorithm, and the optimization results are obtained. In reha-bilitation assistance, the optimal solution of the Pareto solution set can be selected as the optimal path of the manipulator. The results show that the potential optimal solution can be selected from the Pareto optimal solution set by constructing the average fuzzy membership function, to provide an efficient and stable auxiliary path for patients.