【摘要】 针对重力补偿型冗余机械臂的逆解不唯一问题,提出了以改进型粒子群优化算法求解其最优逆解的方法,得到了机械臂在配重砝码位移最小时的逆解.首先通过正运动学分析了配重砝码位移与关节角和舵机补偿力矩之间的关系.在此基础之上,构建了以配重砝码位移最小为优化目标,以位置误差精度为约束条件的逆解方程,并使用改进型粒子群优化算法进行了求解.实验结果表明,该方法得到了机械臂在以配重砝码位移最小为优化目标下的最优逆解,解决了其逆解不唯一问题,对重力补偿型冗余机械臂的后续实验有良好的应用意义.更多还原

【Abstract】 A method based on an improved particle swarm optimization algorithm was proposed to address the non-uniqueness problem of the inverse kinematics of a gravity compensation redundant manipulator and to obtain the optimal inverse kinematics solution for the manipulator with minimum displacement of the counterweight mass.First,the relationship between the displacement of the counterweight mass,joint angles,and servo compensation torque was analyzed using forward kinematics.Based on this,an inverse kinematics equation was constructed with the minimum displacement of the counterweight mass as the optimization objective and the position error accuracy as the constraint condition.An improved particle swarm optimization algorithm was used for the solution.The experimental results show that the optimal inverse kinematics solution for the manipulator with the minimum displacement of the counterweight mass as optimization objective was obtained,and that the non-uniqueness problem of the inverse kinematics was solved.This result is significant for follow-up experiments on the gravity-compensated redundant manipulator.更多还原