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Alternative TitleLoad Estimation of Manipulator Based on the Optimal Sequence of Exciting Poses
侯澈1,2,3; 赵忆文1,2; 张弼1,2; 李英立1,3; 赵新刚1,2
Source Publication机器人
Indexed ByEI ; CSCD
EI Accession number20203309036272
Contribution Rank1
Funding Organization国家重点研发计划(2017YFB1303003,2017YFC0806504) ; 辽宁省博士科研启动基金(20180540131)
Keyword负载估计 静力学模型 粒子群滤波 工业机器人

重力补偿方法广泛地应用于由连杆与旋转机构组成的机器人系统中,更换机器人末端执行器造成了补偿模型的不确定性.针对该问题,提出了一种利用机器人关节力矩与位置信息的负载参数离线辨识方法.基于机器人静力学方法提出了2种负载参数的计算模型,并通过采集机器人在多个静态位姿条件下的关节力矩与位置信息获得负载参数的最小二乘解.进一步,本文针对机器人的辨识位姿选取问题展开研究,提出了同时保证辨识精度与辨识简便性的多目标优化问题,使用多目标粒子群优化方法获得最优辨识位姿.根据辨识后的负载参数,给出了机械臂各关节负载的重力补偿量计算方法.实验结果表明所提方法具有较高的辨识精度,负载质量的辨识误差最小值达到0.007 06 kg,最大值达到0.151 kg,负载质心位置的辨识误差最小值达到0.025 4 m,最大值达到0.122 m,验证了上述方法的可行性与有效性.

Other Abstract

The gravity compensation method is widely used in the robot system composed of the links and the rotating structures. The replacement of the robot end-effector brings uncertainty into the compensation model. For this problem, an offline identification method of load parameters based on joint torque and position information of the robot is proposed. Based on the robot statics method, two calculation models of load parameters are proposed, and the least squares solution of the load parameters is obtained by collecting the joint torque and position information of the manipulator under multiple static poses. Furthermore, the problem of choosing the poses for identification is studied, and a multi-objective optimization problem is proposed to guarantee the accuracy and simplicity of identification simultaneously. The multi-objective particle swarm optimization method is used to obtain the optimal poses for identification. According to the identified load parameters, the calculation method of the load gravity compensation for each joint of the manipulator is given. The experimental results show that the proposed method is of high identification accuracy. The minimum value of the identification error of the load mass is 0.007 06 kg, and the maximum value is 0.151 kg. The minimum value of the identification error of the load centroid position is 0.025 4 m, and the maximum value is 0.122 m. The feasibility and effectiveness of the above method are verified.

Citation statistics
Document Type期刊论文
Corresponding Author赵新刚
Recommended Citation
GB/T 7714
侯澈,赵忆文,张弼,等. 基于最优激励位姿序列的机械臂负载估计[J]. 机器人,2020,42(4):503-512.
APA 侯澈,赵忆文,张弼,李英立,&赵新刚.(2020).基于最优激励位姿序列的机械臂负载估计.机器人,42(4),503-512.
MLA 侯澈,et al."基于最优激励位姿序列的机械臂负载估计".机器人 42.4(2020):503-512.
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