A Novel Human-Like Control Framework for Mobile Medical Service Robot
Recently, as a highly infectious disease of novel coronavirus (COVID-19) has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to trans...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/2905841 |
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| _version_ | 1850212098708078592 |
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| author | Xin Zhang Jiehao Li Wen Qi Xuanyi Zhou Yingbai Hu Hao Quan Zhen Wang |
| author_facet | Xin Zhang Jiehao Li Wen Qi Xuanyi Zhou Yingbai Hu Hao Quan Zhen Wang |
| author_sort | Xin Zhang |
| collection | DOAJ |
| description | Recently, as a highly infectious disease of novel coronavirus (COVID-19) has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to transport medical supplies or meals to patients using robots, but how to teach the robot to the destination and to enter the door like a human is an exciting task. In this paper, a novel human-like control framework for the mobile medical service robot is considered, where a Kinect sensor is used to manage human activity recognition to generate a designed teaching trajectory. Meanwhile, the learning technique of dynamic movement primitives (DMP) with the Gaussian mixture model (GMM) is applied to transfer the skill from humans to robots. A neural-based model predictive tracking controller is implemented to follow the teaching trajectory. Finally, some demonstrations are carried out in a hospital room to illustrate the superiority and effectiveness of the developed framework. |
| format | Article |
| id | doaj-art-8b6b7952502b4f988bfcbf0809f2343e |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8b6b7952502b4f988bfcbf0809f2343e2025-08-20T02:09:25ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/29058412905841A Novel Human-Like Control Framework for Mobile Medical Service RobotXin Zhang0Jiehao Li1Wen Qi2Xuanyi Zhou3Yingbai Hu4Hao Quan5Zhen Wang6Soochow University, Suzhou 215000, ChinaDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, ItalyDepartment of Informatics, Technical University of Munich, Munich 85748, GermanyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, ItalyRecently, as a highly infectious disease of novel coronavirus (COVID-19) has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to transport medical supplies or meals to patients using robots, but how to teach the robot to the destination and to enter the door like a human is an exciting task. In this paper, a novel human-like control framework for the mobile medical service robot is considered, where a Kinect sensor is used to manage human activity recognition to generate a designed teaching trajectory. Meanwhile, the learning technique of dynamic movement primitives (DMP) with the Gaussian mixture model (GMM) is applied to transfer the skill from humans to robots. A neural-based model predictive tracking controller is implemented to follow the teaching trajectory. Finally, some demonstrations are carried out in a hospital room to illustrate the superiority and effectiveness of the developed framework.http://dx.doi.org/10.1155/2020/2905841 |
| spellingShingle | Xin Zhang Jiehao Li Wen Qi Xuanyi Zhou Yingbai Hu Hao Quan Zhen Wang A Novel Human-Like Control Framework for Mobile Medical Service Robot Complexity |
| title | A Novel Human-Like Control Framework for Mobile Medical Service Robot |
| title_full | A Novel Human-Like Control Framework for Mobile Medical Service Robot |
| title_fullStr | A Novel Human-Like Control Framework for Mobile Medical Service Robot |
| title_full_unstemmed | A Novel Human-Like Control Framework for Mobile Medical Service Robot |
| title_short | A Novel Human-Like Control Framework for Mobile Medical Service Robot |
| title_sort | novel human like control framework for mobile medical service robot |
| url | http://dx.doi.org/10.1155/2020/2905841 |
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