基于四元数的工业机器人逆运动学避障求解  

Inverse Kinematics Obstacle Avoidance Solution for Industrial Robot Based on Quaternion

作　　者：董贵荣 张富强[1] 侯丕鸿 韩志星 刘电子 周世生 DONG Gui-rong;ZHANG Fu-qiang;HOU Pi-hong;HAN Zhi-xing;LIU Dian-zi;ZHOU Shi-sheng(Faculty of Printing,Packaging and Digital Media Technology,Xi’an University of Technology,Xi’an 710048,China;Shaanxi Collaborative Innovation Center of Green Intelligent Printing and Packaging,Xi’an University of Technology,Xi’an 710048,China;School of Mechanical Engineering,University of East Anglia,Norwich NR47TJ,England)

机构地区：[1]西安理工大学印刷包装与数字媒体学院,西安710048 [2]西安理工大学陕西省绿色智能印刷包装协同创新中心,西安710048 [3]东英吉利大学机械工程学院,诺里奇NR47TJ

出　　处：《数字印刷》2022年第3期49-56,共8页Digital Printing

摘　　要：随着人工智能技术的发展,工业机器人大量应用于夹取、搬运等工作场景,但由于逆运动学求解复杂,位姿多重解等问题存在,导致机器人鲁棒性差,限制其工业应用范围。为了简化工业机器人逆运动学的求解过程,同时实现复杂障碍物场景下对机器人位姿的精确控制,本研究使用四元数进行机器人位姿解算,并提出一种结合避障模块的改进粒子群(F-PSO)算法。通过与模拟退火算法(SA)、遗传算法(GA)在不同目标位姿下的对比实验分析,证明F-PSO算法表现更为优越,在收敛精度上较传统算法高36.41%以上;在收敛速度上比传统算法快83.82%以上。实验结果表明,本研究提出的F-PSO算法不仅能够精确控制机器人的位姿,而且有效地提高了工作效率,实现了复杂障碍物场景下机器人夹取过程的优化。With the development of artificial intelligence technology,industrial robots are widely used in work scenarios such as gripping and handling.However,due to the complex inverse kinematics solution and the existence of multiple solutions for poses,the robot has poor robustness and its industrial application range is limited.To simplify the solving process of inverse kinematics of industrial robot and realize the accurate control of robot pose in complex obstacle scene,quaternion was used to solve the robot pose,and an improved particle swarm optimization algorithm(F-PSO)was proposed combined with obstacle avoidance module in this paper.Through the comparative experimental analysis with the simulated annealing algorithm(SA)and the genetic algorithm(GA)under different target poses,it was proved that the F-PSO algorithm performed better,and the convergence accuracy was more than 36.41%higher than that of the traditional algorithm.The F-PSO algorithm was more than 83.82%faster than the traditional algorithm.The experimental results showed that the F-PSO algorithm proposed in this paper can not only precisely control the pose of the robot,but also effectively improve the work efficiency and realize the optimization of the robot gripping process in the complex obstacle scene.

关 键 词：夹取机器人 逆运动学求解 四元数 粒子群算法 避障模块 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]