A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction
Human–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we pr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/24/8229 |
| _version_ | 1797500821460484096 |
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| author | Fahad Iqbal Khawaja Akira Kanazawa Jun Kinugawa Kazuhiro Kosuge |
| author_facet | Fahad Iqbal Khawaja Akira Kanazawa Jun Kinugawa Kazuhiro Kosuge |
| author_sort | Fahad Iqbal Khawaja |
| collection | DOAJ |
| description | Human–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker. |
| first_indexed | 2024-03-10T03:09:21Z |
| format | Article |
| id | doaj.art-1b40e78bc2e4479e81bfd29035e47c9f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:09:21Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1b40e78bc2e4479e81bfd29035e47c9f2023-11-23T10:28:32ZengMDPI AGSensors1424-82202021-12-012124822910.3390/s21248229A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion PredictionFahad Iqbal Khawaja0Akira Kanazawa1Jun Kinugawa2Kazuhiro Kosuge3Center for Transformative AI and Robotics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, JapanCenter for Transformative AI and Robotics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, JapanCenter for Transformative AI and Robotics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, JapanCenter for Transformative AI and Robotics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, JapanHuman–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.https://www.mdpi.com/1424-8220/21/24/8229human–robot interactionhuman–robot collaborationcollaborative robotsmotion planningrobot controlhuman motion prediction |
| spellingShingle | Fahad Iqbal Khawaja Akira Kanazawa Jun Kinugawa Kazuhiro Kosuge A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction Sensors human–robot interaction human–robot collaboration collaborative robots motion planning robot control human motion prediction |
| title | A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction |
| title_full | A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction |
| title_fullStr | A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction |
| title_full_unstemmed | A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction |
| title_short | A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction |
| title_sort | human following motion planning and control scheme for collaborative robots based on human motion prediction |
| topic | human–robot interaction human–robot collaboration collaborative robots motion planning robot control human motion prediction |
| url | https://www.mdpi.com/1424-8220/21/24/8229 |
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