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Related Experiment Video

Updated: Dec 18, 2025

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
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Vision Based Wall Following Framework: A Case Study With HSR Robot for Cleaning Application.

Tey Wee Teng1, Prabakaran Veerajagadheswar1, Balakrishnan Ramalingam1

  • 1Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD); Singapore 487372, Singapore.

Sensors (Basel, Switzerland)
|June 14, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a vision-based robotic framework for automated wall cleaning, enhancing infectious disease prevention. The system uses deep learning for accurate surface detection and obstacle avoidance, enabling efficient robotic wall following.

Keywords:
CNNFCN8HSR robot: wall cleaningSSD MobileNetvisual servoingwall following

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Manual cleaning of large wall surfaces is labor-intensive and time-consuming.
  • Robotic solutions for infectious disease control are increasingly important.
  • Current robotic cleaning systems often neglect wall surface cleaning.

Purpose of the Study:

  • To develop a vision-based wall-following framework for robotic wall cleaning.
  • To create an adaptable add-on for existing professional robotic platforms.
  • To improve the efficiency and safety of cleaning frequently touched surfaces.

Main Methods:

  • Utilized a Deep Learning (DL) framework for visual surface detection, classification, and segmentation.
  • Integrated the DL framework with the Toyota Human Support Robot (HSR) platform.
  • Developed a robot control system for precise wall following and obstacle detection.

Main Results:

  • The framework successfully classified and segmented wall/floor surfaces with high accuracy.
  • Obstacles on walls and floors were detected effectively.
  • The robot demonstrated robust wall-following behavior in various scenarios.

Conclusions:

  • The proposed vision-based framework enables automated wall cleaning using robotic platforms.
  • The system offers a viable solution for enhancing hygiene and reducing manual labor in cleaning operations.
  • The framework's adaptability and performance show promise for widespread adoption in professional cleaning.