sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot
Staircase cleaning is a crucial and time-consuming task for maintenance of multistory apartments and commercial buildings. There are many commercially available autonomous cleaning robots in the market for building maintenance, but few of them are designed for staircase cleaning. A key challenge for...
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doaj-3c2a6269b5d34055b3bb3ddbd3e3fc4b2021-09-26T01:24:08ZengMDPI AGSensors1424-82202021-09-01216279627910.3390/s21186279sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable RobotBalakrishnan Ramalingam0Rajesh Elara Mohan1Selvasundari Balakrishnan2Karthikeyan Elangovan3Braulio Félix Gómez4Thejus Pathmakumar5Manojkumar Devarassu6Madan Mohan Rayaguru7Chanthini Baskar8Engineering 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, SingaporeEngineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, SingaporeDepartment of Electrical Engineering, Delhi Technological University, Delhi 110042, IndiaSchool of Electronics, Vellore Institute of Technology Chennai, Vellore 600127, IndiaStaircase cleaning is a crucial and time-consuming task for maintenance of multistory apartments and commercial buildings. There are many commercially available autonomous cleaning robots in the market for building maintenance, but few of them are designed for staircase cleaning. A key challenge for automating staircase cleaning robots involves the design of Environmental Perception Systems (EPS), which assist the robot in determining and navigating staircases. This system also recognizes obstacles and debris for safe navigation and efficient cleaning while climbing the staircase. This work proposes an operational framework leveraging the vision based EPS for the modular re-configurable maintenance robot, called sTetro. The proposed system uses an SSD MobileNet real-time object detection model to recognize staircases, obstacles and debris. Furthermore, the model filters out false detection of staircases by fusion of depth information through the use of a MobileNet and SVM. The system uses a contour detection algorithm to localize the first step of the staircase and depth clustering scheme for obstacle and debris localization. The framework has been deployed on the sTetro robot using the Jetson Nano hardware from NVIDIA and tested with multistory staircases. The experimental results show that the entire framework takes an average of 310 ms to run and achieves an accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>94.32</mn><mo>%</mo></mrow></semantics></math></inline-formula> for staircase recognition tasks and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>93.81</mn><mo>%</mo></mrow></semantics></math></inline-formula> accuracy for obstacle and debris detection tasks during real operation of the robot.https://www.mdpi.com/1424-8220/21/18/6279staircase maintenancereconfigurable robotsTetrodeep learningSSD MobileNetcleaning robot |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Balakrishnan Ramalingam Rajesh Elara Mohan Selvasundari Balakrishnan Karthikeyan Elangovan Braulio Félix Gómez Thejus Pathmakumar Manojkumar Devarassu Madan Mohan Rayaguru Chanthini Baskar |
spellingShingle |
Balakrishnan Ramalingam Rajesh Elara Mohan Selvasundari Balakrishnan Karthikeyan Elangovan Braulio Félix Gómez Thejus Pathmakumar Manojkumar Devarassu Madan Mohan Rayaguru Chanthini Baskar sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot Sensors staircase maintenance reconfigurable robot sTetro deep learning SSD MobileNet cleaning robot |
author_facet |
Balakrishnan Ramalingam Rajesh Elara Mohan Selvasundari Balakrishnan Karthikeyan Elangovan Braulio Félix Gómez Thejus Pathmakumar Manojkumar Devarassu Madan Mohan Rayaguru Chanthini Baskar |
author_sort |
Balakrishnan Ramalingam |
title |
sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot |
title_short |
sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot |
title_full |
sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot |
title_fullStr |
sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot |
title_full_unstemmed |
sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot |
title_sort |
stetro-deep learning powered staircase cleaning and maintenance reconfigurable robot |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-09-01 |
description |
Staircase cleaning is a crucial and time-consuming task for maintenance of multistory apartments and commercial buildings. There are many commercially available autonomous cleaning robots in the market for building maintenance, but few of them are designed for staircase cleaning. A key challenge for automating staircase cleaning robots involves the design of Environmental Perception Systems (EPS), which assist the robot in determining and navigating staircases. This system also recognizes obstacles and debris for safe navigation and efficient cleaning while climbing the staircase. This work proposes an operational framework leveraging the vision based EPS for the modular re-configurable maintenance robot, called sTetro. The proposed system uses an SSD MobileNet real-time object detection model to recognize staircases, obstacles and debris. Furthermore, the model filters out false detection of staircases by fusion of depth information through the use of a MobileNet and SVM. The system uses a contour detection algorithm to localize the first step of the staircase and depth clustering scheme for obstacle and debris localization. The framework has been deployed on the sTetro robot using the Jetson Nano hardware from NVIDIA and tested with multistory staircases. The experimental results show that the entire framework takes an average of 310 ms to run and achieves an accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>94.32</mn><mo>%</mo></mrow></semantics></math></inline-formula> for staircase recognition tasks and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>93.81</mn><mo>%</mo></mrow></semantics></math></inline-formula> accuracy for obstacle and debris detection tasks during real operation of the robot. |
topic |
staircase maintenance reconfigurable robot sTetro deep learning SSD MobileNet cleaning robot |
url |
https://www.mdpi.com/1424-8220/21/18/6279 |
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