Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application
Periodic cleaning of all frequently touched social areas such as walls, doors, locks, handles, windows has become the first line of defense against all infectious diseases. Among those, cleaning of large wall areas manually is always tedious, time-consuming, and astounding task. Although numerous cl...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/11/3298 |
| _version_ | 1797565643289001984 |
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| author | Tey Wee Teng Prabakaran Veerajagadheswar Balakrishnan Ramalingam Jia Yin Rajesh Elara Mohan Braulio Félix Gómez |
| author_facet | Tey Wee Teng Prabakaran Veerajagadheswar Balakrishnan Ramalingam Jia Yin Rajesh Elara Mohan Braulio Félix Gómez |
| author_sort | Tey Wee Teng |
| collection | DOAJ |
| description | Periodic cleaning of all frequently touched social areas such as walls, doors, locks, handles, windows has become the first line of defense against all infectious diseases. Among those, cleaning of large wall areas manually is always tedious, time-consuming, and astounding task. Although numerous cleaning companies are interested in deploying robotic cleaning solutions, they are mostly not addressing wall cleaning. To this end, we are proposing a new vision-based wall following framework that acts as an add-on for any professional robotic platform to perform wall cleaning. The proposed framework uses Deep Learning (DL) framework to visually detect, classify, and segment the wall/floor surface and instructs the robot to wall follow to execute the cleaning task. Also, we summarized the system architecture of Toyota Human Support Robot (HSR), which has been used as our testing platform. We evaluated the performance of the proposed framework on HSR robot under various defined scenarios. Our experimental results indicate that the proposed framework could successfully classify and segment the wall/floor surface and also detect the obstacle on wall and floor with high detection accuracy and demonstrates a robust behavior of wall following. |
| first_indexed | 2024-03-10T19:16:01Z |
| format | Article |
| id | doaj.art-62ddbe2cdfbc4ad0b2cf2cf7df94a062 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:16:01Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-62ddbe2cdfbc4ad0b2cf2cf7df94a0622023-11-20T03:24:40ZengMDPI AGSensors1424-82202020-06-012011329810.3390/s20113298Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning ApplicationTey Wee Teng0Prabakaran Veerajagadheswar1Balakrishnan Ramalingam2Jia Yin3Rajesh Elara Mohan4Braulio Félix Gómez5Engineering 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, SingaporeEngineering 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, SingaporeEngineering 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, SingaporePeriodic cleaning of all frequently touched social areas such as walls, doors, locks, handles, windows has become the first line of defense against all infectious diseases. Among those, cleaning of large wall areas manually is always tedious, time-consuming, and astounding task. Although numerous cleaning companies are interested in deploying robotic cleaning solutions, they are mostly not addressing wall cleaning. To this end, we are proposing a new vision-based wall following framework that acts as an add-on for any professional robotic platform to perform wall cleaning. The proposed framework uses Deep Learning (DL) framework to visually detect, classify, and segment the wall/floor surface and instructs the robot to wall follow to execute the cleaning task. Also, we summarized the system architecture of Toyota Human Support Robot (HSR), which has been used as our testing platform. We evaluated the performance of the proposed framework on HSR robot under various defined scenarios. Our experimental results indicate that the proposed framework could successfully classify and segment the wall/floor surface and also detect the obstacle on wall and floor with high detection accuracy and demonstrates a robust behavior of wall following.https://www.mdpi.com/1424-8220/20/11/3298wall followingCNNHSR robot: wall cleaningFCN8SSD MobileNetvisual servoing |
| spellingShingle | Tey Wee Teng Prabakaran Veerajagadheswar Balakrishnan Ramalingam Jia Yin Rajesh Elara Mohan Braulio Félix Gómez Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application Sensors wall following CNN HSR robot: wall cleaning FCN8 SSD MobileNet visual servoing |
| title | Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application |
| title_full | Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application |
| title_fullStr | Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application |
| title_full_unstemmed | Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application |
| title_short | Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application |
| title_sort | vision based wall following framework a case study with hsr robot for cleaning application |
| topic | wall following CNN HSR robot: wall cleaning FCN8 SSD MobileNet visual servoing |
| url | https://www.mdpi.com/1424-8220/20/11/3298 |
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