Table Cleaning Task by Human Support Robot Using Deep Learning Technique

This work presents a table cleaning and inspection method using a Human Support Robot (HSR) which can operate in a typical food court setting. The HSR is able to perform a cleanliness inspection and also clean the food litter on the table by implementing a deep learning technique and planner framewo...

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Main Authors: Jia Yin, Koppaka Ganesh Sai Apuroop, Yokhesh Krishnasamy Tamilselvam, Rajesh Elara Mohan, Balakrishnan Ramalingam, Anh Vu Le
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/6/1698
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author Jia Yin
Koppaka Ganesh Sai Apuroop
Yokhesh Krishnasamy Tamilselvam
Rajesh Elara Mohan
Balakrishnan Ramalingam
Anh Vu Le
author_facet Jia Yin
Koppaka Ganesh Sai Apuroop
Yokhesh Krishnasamy Tamilselvam
Rajesh Elara Mohan
Balakrishnan Ramalingam
Anh Vu Le
author_sort Jia Yin
collection DOAJ
description This work presents a table cleaning and inspection method using a Human Support Robot (HSR) which can operate in a typical food court setting. The HSR is able to perform a cleanliness inspection and also clean the food litter on the table by implementing a deep learning technique and planner framework. A lightweight Deep Convolutional Neural Network (DCNN) has been proposed to recognize the food litter on top of the table. In addition, the planner framework was proposed to HSR for accomplishing the table cleaning task which generates the cleaning path according to the detection of food litter and then the cleaning action is carried out. The effectiveness of the food litter detection module is verified with the cleanliness inspection task using Toyota HSR, and its detection results are verified with standard quality metrics. The experimental results show that the food litter detection module achieves an average of <inline-formula> <math display="inline"> <semantics> <mrow> <mn>96</mn> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> detection accuracy, which is more suitable for deploying the HSR robots for performing the cleanliness inspection and also helps to select the different cleaning modes. Further, the planner part has been tested through the table cleaning tasks. The experimental results show that the planner generated the cleaning path in real time and its generated path is optimal which reduces the cleaning time by grouping based cleaning action for removing the food litters from the table.
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spelling doaj.art-f6b3fcd715c744b79d8ed0bde0eece272022-12-22T04:01:26ZengMDPI AGSensors1424-82202020-03-01206169810.3390/s20061698s20061698Table Cleaning Task by Human Support Robot Using Deep Learning TechniqueJia Yin0Koppaka Ganesh Sai Apuroop1Yokhesh Krishnasamy Tamilselvam2Rajesh Elara Mohan3Balakrishnan Ramalingam4Anh Vu Le5Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, SingaporeEngineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, SingaporeDepartment of Electrical Engineering, Clemson University, Clemson, SC 29631, USAEngineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, SingaporeEngineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, SingaporeOptoelectronics Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, VietnamThis work presents a table cleaning and inspection method using a Human Support Robot (HSR) which can operate in a typical food court setting. The HSR is able to perform a cleanliness inspection and also clean the food litter on the table by implementing a deep learning technique and planner framework. A lightweight Deep Convolutional Neural Network (DCNN) has been proposed to recognize the food litter on top of the table. In addition, the planner framework was proposed to HSR for accomplishing the table cleaning task which generates the cleaning path according to the detection of food litter and then the cleaning action is carried out. The effectiveness of the food litter detection module is verified with the cleanliness inspection task using Toyota HSR, and its detection results are verified with standard quality metrics. The experimental results show that the food litter detection module achieves an average of <inline-formula> <math display="inline"> <semantics> <mrow> <mn>96</mn> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> detection accuracy, which is more suitable for deploying the HSR robots for performing the cleanliness inspection and also helps to select the different cleaning modes. Further, the planner part has been tested through the table cleaning tasks. The experimental results show that the planner generated the cleaning path in real time and its generated path is optimal which reduces the cleaning time by grouping based cleaning action for removing the food litters from the table.https://www.mdpi.com/1424-8220/20/6/1698inspectiontable cleaningdeep learningcnnhuman support robotfood litter detection
spellingShingle Jia Yin
Koppaka Ganesh Sai Apuroop
Yokhesh Krishnasamy Tamilselvam
Rajesh Elara Mohan
Balakrishnan Ramalingam
Anh Vu Le
Table Cleaning Task by Human Support Robot Using Deep Learning Technique
Sensors
inspection
table cleaning
deep learning
cnn
human support robot
food litter detection
title Table Cleaning Task by Human Support Robot Using Deep Learning Technique
title_full Table Cleaning Task by Human Support Robot Using Deep Learning Technique
title_fullStr Table Cleaning Task by Human Support Robot Using Deep Learning Technique
title_full_unstemmed Table Cleaning Task by Human Support Robot Using Deep Learning Technique
title_short Table Cleaning Task by Human Support Robot Using Deep Learning Technique
title_sort table cleaning task by human support robot using deep learning technique
topic inspection
table cleaning
deep learning
cnn
human support robot
food litter detection
url https://www.mdpi.com/1424-8220/20/6/1698
work_keys_str_mv AT jiayin tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique
AT koppakaganeshsaiapuroop tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique
AT yokheshkrishnasamytamilselvam tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique
AT rajeshelaramohan tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique
AT balakrishnanramalingam tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique
AT anhvule tablecleaningtaskbyhumansupportrobotusingdeeplearningtechnique