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A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework.
Ramalingam, Balakrishnan; Yin, Jia; Rajesh Elara, Mohan; Tamilselvam, Yokhesh Krishnasamy; Mohan Rayguru, Madan; Muthugala, M A Viraj J; Félix Gómez, Braulio.
  • Ramalingam B; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
  • Yin J; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
  • Rajesh Elara M; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
  • Tamilselvam YK; Department of Electrical Engineering, University of Western Ontario, London, ON N6A 3K7, Canada.
  • Mohan Rayguru M; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
  • Muthugala MAVJ; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
  • Félix Gómez B; Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
Sensors (Basel) ; 20(12)2020 Jun 23.
Article in English | MEDLINE | ID: covidwho-610868
ABSTRACT
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that are prone to be contamination. Automation of the door-handle cleaning task is not only important for ensuring safety, but also to improve efficiency. This work proposes an AI-enabled framework for automating cleaning tasks through a Human Support Robot (HSR). The overall cleaning process involves mobile base motion, door-handle detection, and control of the HSR manipulator for the completion of the cleaning tasks. The detection part exploits a deep-learning technique to classify the image space, and provides a set of coordinates for the robot. The cooperative control between the spraying and wiping is developed in the Robotic Operating System. The control module uses the information obtained from the detection module to generate a task/operational space for the robot, along with evaluating the desired position to actuate the manipulators. The complete strategy is validated through numerical simulations, and experiments on a Toyota HSR platform.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Robotics / Disinfection / Coronavirus Infections / Pandemics / Betacoronavirus Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Humans Language: English Year: 2020 Document Type: Article Affiliation country: S20123543

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Robotics / Disinfection / Coronavirus Infections / Pandemics / Betacoronavirus Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Humans Language: English Year: 2020 Document Type: Article Affiliation country: S20123543