Jixie chuandong (Jan 2022)
Trajectory Optimization of Manipulator based on Adaptive Transformation Bat Algorithm
Abstract
In order to improve the work efficiency of the manipulator while reducing the energy loss and impact， a trajectory optimization method based on the adaptive transformation bat algorithm （ATBA） is proposed. The trajectory model of the manipulator is established by using quintic polynomial interpolation; the ATBA is obtained by adding dynamic disturbance coefficients to the local search of the standard bat algorithm （BA）， and improving the conversion strategy of global search and local search at the same time. Optimize the motion trajectory of the manipulator with time， energy consumption and impact as the optimization goals. The simulation analysis of the six-degree-of-freedom manipulator shows that the trajectory optimization method can effectively perform multi-objective optimization and obtain the ideal Pareto optimal solution set. The normalized weight objective function is constructed through actual working conditions， and the desired solution can be selected by it. This optimization algorithm can improve the smoothness of trajectory， speed， acceleration and the operating efficiency of the manipulator better.
