Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations
The purpose of this study was to ensure the compliance and safety of a robot’s movements during interactions with the external environment. This paper proposes a control strategy for learning variable impedance characteristics from multiple sets of demonstration trajectories. This strategy can adapt...
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MDPI AG
2024-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/12/23/3840 |
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| author | Feifei Zhong Lingyan Hu Yingli Chen |
| author_facet | Feifei Zhong Lingyan Hu Yingli Chen |
| author_sort | Feifei Zhong |
| collection | DOAJ |
| description | The purpose of this study was to ensure the compliance and safety of a robot’s movements during interactions with the external environment. This paper proposes a control strategy for learning variable impedance characteristics from multiple sets of demonstration trajectories. This strategy can adapt to the control of different joints by adjusting the parameters of the variable impedance control policy. Firstly, multiple sets of demonstration trajectories are aligned on the time axis using Dynamic Time Warping. Subsequently, the variance obtained through Gaussian Mixture Regression and a variable impedance strategy based on an improved Softplus function are employed to represent the variance as the variable impedance characteristic of the robotic arm, thereby enabling variable impedance control for the robotic arm. The experiments conducted on a self-designed robotic arm demonstrate that, compared to other variable impedance methods, the motion accuracy of the trajectories of joints 1 to 4 improved by 57.23%, 3.66%, 5.36%, and 20.16%, respectively. Additionally, a stiffness-variable segmented generalization method based on Dynamic Movement Primitive is proposed to achieve variable impedance control in various task environments. This strategy fulfills the requirements for compliance and safety during robot interactions. |
| format | Article |
| id | doaj-art-ea698c27403e461996d8d41eb98f505b |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-ea698c27403e461996d8d41eb98f505b2025-08-20T02:38:39ZengMDPI AGMathematics2227-73902024-12-011223384010.3390/math12233840Robot Variable Impedance Control and Generalizing from Human–Robot Interaction DemonstrationsFeifei Zhong0Lingyan Hu1Yingli Chen2Anhui Research Center of Generic Technology in Photovoltaic Industry, Fuyang Normal University, Fuyang 236037, ChinaSchool of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Architectural Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaThe purpose of this study was to ensure the compliance and safety of a robot’s movements during interactions with the external environment. This paper proposes a control strategy for learning variable impedance characteristics from multiple sets of demonstration trajectories. This strategy can adapt to the control of different joints by adjusting the parameters of the variable impedance control policy. Firstly, multiple sets of demonstration trajectories are aligned on the time axis using Dynamic Time Warping. Subsequently, the variance obtained through Gaussian Mixture Regression and a variable impedance strategy based on an improved Softplus function are employed to represent the variance as the variable impedance characteristic of the robotic arm, thereby enabling variable impedance control for the robotic arm. The experiments conducted on a self-designed robotic arm demonstrate that, compared to other variable impedance methods, the motion accuracy of the trajectories of joints 1 to 4 improved by 57.23%, 3.66%, 5.36%, and 20.16%, respectively. Additionally, a stiffness-variable segmented generalization method based on Dynamic Movement Primitive is proposed to achieve variable impedance control in various task environments. This strategy fulfills the requirements for compliance and safety during robot interactions.https://www.mdpi.com/2227-7390/12/23/3840variable impedancedemonstration trajectoriesDynamic Movement Primitiveimproved Softplus functionimpedance control |
| spellingShingle | Feifei Zhong Lingyan Hu Yingli Chen Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations Mathematics variable impedance demonstration trajectories Dynamic Movement Primitive improved Softplus function impedance control |
| title | Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations |
| title_full | Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations |
| title_fullStr | Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations |
| title_full_unstemmed | Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations |
| title_short | Robot Variable Impedance Control and Generalizing from Human–Robot Interaction Demonstrations |
| title_sort | robot variable impedance control and generalizing from human robot interaction demonstrations |
| topic | variable impedance demonstration trajectories Dynamic Movement Primitive improved Softplus function impedance control |
| url | https://www.mdpi.com/2227-7390/12/23/3840 |
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