Robust kinematic calibration for improving collaboration accuracy of dual-arm manipulators with experimental validation
•A scheme of collaborative accuracy is established for calibration of dual-arm robots.•Orientation accuracy is guaranteed by minimizing the maximum distance error.•Robustness of calibration procedure is enhanced by minimax searching.•Experimental comparisons validate the superiority of the proposed...
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| Published in: | Measurement : journal of the International Measurement Confederation Vol. 155; p. 107524 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.04.2020
Elsevier Science Ltd |
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| ISSN: | 0263-2241, 1873-412X |
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| Abstract | •A scheme of collaborative accuracy is established for calibration of dual-arm robots.•Orientation accuracy is guaranteed by minimizing the maximum distance error.•Robustness of calibration procedure is enhanced by minimax searching.•Experimental comparisons validate the superiority of the proposed method.
Kinematic calibration has been widely employed for manipulators to promote their performance characteristics. For a dual-arm manipulator, most of the research attentions are paid to improving the absolute positioning accuracy. However, collaborative accuracy plays a critical role in mutual operations between the two arms. For example, in dangerous chemical experiments, the dual-arm manipulator is often demanded to grab a target object with the two hands, or re-grasp a test tube from one hand to the other, where the inferior collaborative accuracy may lead to the failure of experiments. Hence, in this paper, collaborative accuracy of dual-arm manipulators is well defined and fully considered as the objective for calibration. Robustness of the calibration is further guaranteed by minimizing the maximum distance error. The formulated problem is not a typical convex optimization, and gradient search algorithm does not work well for this problem. With researches on optimization moving forward, recent advances in nonlinear optimization are employed to seek for the solution effectively, and it is found that the minimax problem can be approximately linearized to a sequence quadratic programming (SQP) problem. Furthermore, a primal-dual subgradient algorithm is applied for solving the SQP problem with a fast local convergence. Finally, in order to verify the superiority of the proposed method, an experiment is performed on an IRB 14000 manipulator, and corresponding outcomes indicate that the RMS collaborative positioning and the orientation accuracies are significantly improved by 90.60% and 91.42%. To the best of our knowledge, our method has reached the best collaborative accuracy compared with existing works (Wang et al., 2014; Roncone et al., 2014; Motta et al., 2001). |
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| AbstractList | •A scheme of collaborative accuracy is established for calibration of dual-arm robots.•Orientation accuracy is guaranteed by minimizing the maximum distance error.•Robustness of calibration procedure is enhanced by minimax searching.•Experimental comparisons validate the superiority of the proposed method.
Kinematic calibration has been widely employed for manipulators to promote their performance characteristics. For a dual-arm manipulator, most of the research attentions are paid to improving the absolute positioning accuracy. However, collaborative accuracy plays a critical role in mutual operations between the two arms. For example, in dangerous chemical experiments, the dual-arm manipulator is often demanded to grab a target object with the two hands, or re-grasp a test tube from one hand to the other, where the inferior collaborative accuracy may lead to the failure of experiments. Hence, in this paper, collaborative accuracy of dual-arm manipulators is well defined and fully considered as the objective for calibration. Robustness of the calibration is further guaranteed by minimizing the maximum distance error. The formulated problem is not a typical convex optimization, and gradient search algorithm does not work well for this problem. With researches on optimization moving forward, recent advances in nonlinear optimization are employed to seek for the solution effectively, and it is found that the minimax problem can be approximately linearized to a sequence quadratic programming (SQP) problem. Furthermore, a primal-dual subgradient algorithm is applied for solving the SQP problem with a fast local convergence. Finally, in order to verify the superiority of the proposed method, an experiment is performed on an IRB 14000 manipulator, and corresponding outcomes indicate that the RMS collaborative positioning and the orientation accuracies are significantly improved by 90.60% and 91.42%. To the best of our knowledge, our method has reached the best collaborative accuracy compared with existing works (Wang et al., 2014; Roncone et al., 2014; Motta et al., 2001). Kinematic calibration has been widely employed for manipulators to promote their performance characteristics. For a dual-arm manipulator, most of the research attentions are paid to improving the absolute positioning accuracy. However, collaborative accuracy plays a critical role in mutual operations between the two arms. For example, in dangerous chemical experiments, the dual-arm manipulator is often demanded to grab a target object with the two hands, or re-grasp a test tube from one hand to the other, where the inferior collaborative accuracy may lead to the failure of experiments. Hence, in this paper, collaborative accuracy of dual-arm manipulators is well defined and fully considered as the objective for calibration. Robustness of the calibration is further guaranteed by minimizing the maximum distance error. The formulated problem is not a typical convex optimization, and gradient search algorithm does not work well for this problem. With researches on optimization moving forward, recent advances in nonlinear optimization are employed to seek for the solution effectively, and it is found that the minimax problem can be approximately linearized to a sequence quadratic programming (SQP) problem. Furthermore, a primal-dual subgradient algorithm is applied for solving the SQP problem with a fast local convergence. Finally, in order to verify the superiority of the proposed method, an experiment is performed on an IRB 14000 manipulator, and corresponding outcomes indicate that the RMS collaborative positioning and the orientation accuracies are significantly improved by 90.60% and 91.42%. To the best of our knowledge, our method has reached the best collaborative accuracy compared with existing works (Wang et al., 2014; Roncone et al., 2014; Motta et al., 2001). |
| ArticleNumber | 107524 |
| Author | Li, Shuai Li, Chao Chen, Zhangwei Mao, Chentao Zhang, Xiang |
| Author_xml | – sequence: 1 givenname: Chentao surname: Mao fullname: Mao, Chentao email: mct@zju.edu.cn organization: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China – sequence: 2 givenname: Shuai surname: Li fullname: Li, Shuai organization: College of Engineering, Swansea University, Swansea, UK – sequence: 3 givenname: Zhangwei surname: Chen fullname: Chen, Zhangwei organization: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China – sequence: 4 givenname: Xiang surname: Zhang fullname: Zhang, Xiang organization: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China – sequence: 5 givenname: Chao surname: Li fullname: Li, Chao organization: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China |
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| Keywords | Robustness Dual-arm manipulators Relative accuracy Kinematic calibration Collaborative accuracy |
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| Snippet | •A scheme of collaborative accuracy is established for calibration of dual-arm robots.•Orientation accuracy is guaranteed by minimizing the maximum distance... Kinematic calibration has been widely employed for manipulators to promote their performance characteristics. For a dual-arm manipulator, most of the research... |
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| SubjectTerms | Algorithms Calibration Collaborative accuracy Computational geometry Convexity Dual-arm manipulators Kinematic calibration Kinematics Minimax technique Optimization Quadratic programming Relative accuracy Robustness Search algorithms |
| Title | Robust kinematic calibration for improving collaboration accuracy of dual-arm manipulators with experimental validation |
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