A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection
Safety during physical human–robot interaction is the most basic requirement for robots. Collision detection without additional sensors is an economically feasible way to ensure it. In contrast, current collision detection approaches have an unavoidable trade-off between sensitivity to collisions, s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/10/9/818 |
| _version_ | 1827659363524804608 |
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| author | Shike Long Xuanju Dang Shanlin Sun Yongjun Wang Mingzhen Gui |
| author_facet | Shike Long Xuanju Dang Shanlin Sun Yongjun Wang Mingzhen Gui |
| author_sort | Shike Long |
| collection | DOAJ |
| description | Safety during physical human–robot interaction is the most basic requirement for robots. Collision detection without additional sensors is an economically feasible way to ensure it. In contrast, current collision detection approaches have an unavoidable trade-off between sensitivity to collisions, signal smoothness, and immunity to measurement noise. In this paper, we present a novel sliding mode momentum observer (NSOMO) for detecting collisions between robots and humans, including dynamic and quasistatic collisions. The collision detection method starts with a dynamic model of the robot and derives a generalized momentum-based state equation. Then a new reaching law is devised, based on which NSOMO is constructed by fusing momentum, achieving higher bandwidth and noise immunity of observation. Finally, a time-varying dynamic threshold (TVDT) model is designed to distinguish between collision signals and the estimated lumped disturbance. Its coefficients are obtained through offline data recognition. The TVDT with NSOMO enables fast and reliable collision detection and allows collision position assessment. Simulation experiments and hardware tests of the 7-DOF collaborative robot are implemented to illustrate this proposed method’s effectiveness. |
| first_indexed | 2024-03-09T23:20:24Z |
| format | Article |
| id | doaj.art-4a8f09b5c14f48ceb77c9cae10491aed |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-09T23:20:24Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-4a8f09b5c14f48ceb77c9cae10491aed2023-11-23T17:27:25ZengMDPI AGMachines2075-17022022-09-0110981810.3390/machines10090818A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision DetectionShike Long0Xuanju Dang1Shanlin Sun2Yongjun Wang3Mingzhen Gui4School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, ChinaSchool of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, ChinaSchool of Aeronautics and Astronautics, Guilin University of Aerospace technology, Guilin 541004, ChinaSchool of Aeronautics and Astronautics, Guilin University of Aerospace technology, Guilin 541004, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSafety during physical human–robot interaction is the most basic requirement for robots. Collision detection without additional sensors is an economically feasible way to ensure it. In contrast, current collision detection approaches have an unavoidable trade-off between sensitivity to collisions, signal smoothness, and immunity to measurement noise. In this paper, we present a novel sliding mode momentum observer (NSOMO) for detecting collisions between robots and humans, including dynamic and quasistatic collisions. The collision detection method starts with a dynamic model of the robot and derives a generalized momentum-based state equation. Then a new reaching law is devised, based on which NSOMO is constructed by fusing momentum, achieving higher bandwidth and noise immunity of observation. Finally, a time-varying dynamic threshold (TVDT) model is designed to distinguish between collision signals and the estimated lumped disturbance. Its coefficients are obtained through offline data recognition. The TVDT with NSOMO enables fast and reliable collision detection and allows collision position assessment. Simulation experiments and hardware tests of the 7-DOF collaborative robot are implemented to illustrate this proposed method’s effectiveness.https://www.mdpi.com/2075-1702/10/9/818collision detectionhuman–robot interactionreaching lawsliding mode momentum observer |
| spellingShingle | Shike Long Xuanju Dang Shanlin Sun Yongjun Wang Mingzhen Gui A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection Machines collision detection human–robot interaction reaching law sliding mode momentum observer |
| title | A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection |
| title_full | A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection |
| title_fullStr | A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection |
| title_full_unstemmed | A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection |
| title_short | A Novel Sliding Mode Momentum Observer for Collaborative Robot Collision Detection |
| title_sort | novel sliding mode momentum observer for collaborative robot collision detection |
| topic | collision detection human–robot interaction reaching law sliding mode momentum observer |
| url | https://www.mdpi.com/2075-1702/10/9/818 |
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