Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks
Inspired by Model Predictive Interaction Control (MPIC), this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid–soft heterogeneous contact task...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Biomimetic Intelligence and Robotics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667379724000524 |
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| _version_ | 1832595293591306240 |
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| author | Haochen Zheng Xueqian Zhai Hongmin Wu Jia Pan Zhihao Xu Xuefeng Zhou |
| author_facet | Haochen Zheng Xueqian Zhai Hongmin Wu Jia Pan Zhihao Xu Xuefeng Zhou |
| author_sort | Haochen Zheng |
| collection | DOAJ |
| description | Inspired by Model Predictive Interaction Control (MPIC), this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid–soft heterogeneous contact tasks. Within the MPIC, robot dynamics are linearized, and Extended Kalman Filters are used for the online estimation of geometry-aware parameters. Meanwhile, a geometry-aware Hertz contact model is introduced for the online estimation of contact forces. We then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization MPC. Experimental validations were designed for two contact modes: “single-point contact” and “continuous contact”, involving materials with four different Young’s moduli and tested in human arm “relaxation–contraction” task. Results indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee safety. Our method reduces the maximum impact force by 50% and decreases the average force error by 42%. The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid, soft, and deformable objects. |
| format | Article |
| id | doaj-art-ebd5744d5a6348f7970d09a5f0347d99 |
| institution | Kabale University |
| issn | 2667-3797 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Biomimetic Intelligence and Robotics |
| spelling | doaj-art-ebd5744d5a6348f7970d09a5f0347d992025-01-19T06:26:55ZengElsevierBiomimetic Intelligence and Robotics2667-37972025-03-0151100194Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasksHaochen Zheng0Xueqian Zhai1Hongmin Wu2Jia Pan3Zhihao Xu4Xuefeng Zhou5Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou 510070, China; School of Rail Transportation, Wuyi University, Jiangmen 529020, ChinaInstitute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou 510070, ChinaInstitute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou 510070, China; Corresponding author.Department of Computer Science, The University of Hong Kong, Hong Kong 999077, ChinaInstitute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou 510070, ChinaInstitute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou 510070, ChinaInspired by Model Predictive Interaction Control (MPIC), this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid–soft heterogeneous contact tasks. Within the MPIC, robot dynamics are linearized, and Extended Kalman Filters are used for the online estimation of geometry-aware parameters. Meanwhile, a geometry-aware Hertz contact model is introduced for the online estimation of contact forces. We then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization MPC. Experimental validations were designed for two contact modes: “single-point contact” and “continuous contact”, involving materials with four different Young’s moduli and tested in human arm “relaxation–contraction” task. Results indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee safety. Our method reduces the maximum impact force by 50% and decreases the average force error by 42%. The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid, soft, and deformable objects.http://www.sciencedirect.com/science/article/pii/S2667379724000524Heterogeneous contactInteraction model estimationCoordination optimizationModel Predictive Control |
| spellingShingle | Haochen Zheng Xueqian Zhai Hongmin Wu Jia Pan Zhihao Xu Xuefeng Zhou Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks Biomimetic Intelligence and Robotics Heterogeneous contact Interaction model estimation Coordination optimization Model Predictive Control |
| title | Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks |
| title_full | Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks |
| title_fullStr | Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks |
| title_full_unstemmed | Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks |
| title_short | Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks |
| title_sort | interaction model estimation based robotic force position coordinated optimization for rigid soft heterogeneous contact tasks |
| topic | Heterogeneous contact Interaction model estimation Coordination optimization Model Predictive Control |
| url | http://www.sciencedirect.com/science/article/pii/S2667379724000524 |
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