Abstract：In the field of aeronautical and astronautical assembly, the six–dimensional force sensors installed on the end of robot is commonly used to derive external forces, which is one of the key technologies to realize the compliance control of industrial robots, but the presence of loads will interfere the perception of external forces. To compensate the gravity of end load of industrial robots, a genetic algorithm-based gravity compensation optimization algorithm is proposed. Based on the least squared method, this method considers the influence of force sensor installation deflection angle on compensation effect, and an optimal solution model is established with the objective of minimizing the sum of squared error, by using genetic algorithm. As a result, the installation deflection angle of force sensor can be estimated without use of measuring instruments, and the accuracy of gravity compensation can be improved. In the meantime, the system errors are reduced effectively by designing specific robot measuring attitude. The experiments show that arbitrary angles of the installation deflection angle can be compensated by optimization algorithm. Compared with before compensation, maximum gravity compensation errors in each direction and average gravity compensation errors are both generally reduced.
李根，李鹏程，吴超，沈烨. 基于遗传算法的机器人负载重力补偿优化算法研究[J]. 航空制造技术, 2021, 64(5): 52-59.
LI Gen, LI Pengcheng, WU Chao, SHEN Ye. Research on Optimization Algorithm of Robot Load Gravity Compensation Based on Genetic Algorithm. Aeronautical Manufacturing Technology, 2021, 64(5): 52-59.
2021, 
