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...

Full description

Saved in:
Bibliographic Details
Main Authors: Xin Zhang, Jiehao Li, Wen Qi, Xuanyi Zhou, Yingbai Hu, Hao Quan, Zhen Wang
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/2905841
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850212098708078592
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
work_keys_str_mv AT xinzhang anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT jiehaoli anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT wenqi anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT xuanyizhou anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT yingbaihu anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT haoquan anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT zhenwang anovelhumanlikecontrolframeworkformobilemedicalservicerobot
AT xinzhang novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT jiehaoli novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT wenqi novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT xuanyizhou novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT yingbaihu novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT haoquan novelhumanlikecontrolframeworkformobilemedicalservicerobot
AT zhenwang novelhumanlikecontrolframeworkformobilemedicalservicerobot