Joints Trajectory Planning of Robot Based on Slime Mould Whale Optimization Algorithm

Abstract

The joints running trajectory of a robot directly affects it's working efficiency, stationarity and working quality. To solve the problems of slow convergence speed and weak global search ability in the current commonly used joint trajectory optimization algorithms, a joint trajectory planning method based on slime mould whale optimization algorithm (SMWOA) was researched, which could obtain the joint trajectory within a short time and with low energy consumption. On the basis of analyses of the whale optimization algorithm (WOA) and slime mould algorithm (SMA) in detail, the SMWOA was proposed by combining the two methods. By adjusting dynamic parameters and introducing dynamic weights, the proposed SMWOA increased the probability of obtaining the global optimal solution. The optimized results of 15 benchmark functions verified that the optimization accuracy of the SMWOA is clearly better than that of other classical algorithms. An experiment was carried out in which this algorithm was applied to joint trajectory optimization. Taking 6-DOF UR5 manipulator as an example, the results show that the optimized running time of the joints is reduced by 37.674% compared with that before optimization. The efficiency of robot joint motion was improved. This study provides a theoretical basis for the optimization of other engineering fields.