Robot Workspace Optimization based on Monte Carlo Method and Multi Island Genetic Algorithm
Keywords:Monte Carlo; multi island genetic algorithm: workspace; optimization
Workspace analysis is an indispensable part of robot research. The workspace volume is an important factor to measure the working ability of parallel robot. In order to maximize the workspace of parallel robot, this paper solves the workspace of robot by using Monte Carlo method, and obtains that the workspace volume is 2.142×106 mm3, which is optimized by the multi Island genetic algorithm in the global optimization algorithm. After optimization, the workspace volume increases to 8.25×106 mm3, the volume of workspace before and after optimization is increased by 3.85 times. The influence of various structural parameters of the parallel robot on the workspace volume is analyzed and studied. It is obtained that the rod length ratio of the connecting rod and the driving rod has the greatest influence on the workspace volume, followed by the ratio of the center angle of the long and short sides, and the radius of the moving platform has the least influence. Furthermore, the influence of single parameter on the workspace volume is analyzed. When other parameters remain unchanged, the maximum workspace volume can be achieved when the rod length ratio of connecting rod and driving rod is 1.25, or the ratio of center angle of long and short sides is 1.53.