Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application

Sensors
Tey Wee TengBraulio Félix Gómez

Abstract

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 follo...Continue Reading

References

Sep 1, 2012·IEEE Transactions on Neural Networks and Learning Systems·Yimin YangXiaofang Yuan
Jun 8, 2018·Data in Brief·Fereshteh S BashiriAhmad P Tafti
Nov 17, 2019·Mathematical Biosciences and Engineering : MBE·Li Yong MaHai Bin Huang

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Citations

Sep 19, 2020·Sensors·Balakrishnan RamalingamYokhesh Krishnasamy Tamilselvam
May 1, 2021·Sensors·Balakrishnan RamalingamSelvasundari Subramanian

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Methods Mentioned

BETA
feature extraction

Software Mentioned

MobileNet
MobilNet
ROS
Tensor
Adlatus
SSD
flow
RedNet
SSD mobileNet
Yolo

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