Buildings (Apr 2024)

A Framework for Auditing Robot-Inclusivity of Indoor Environments Based on Lighting Condition

  • Zimou Zeng,
  • Matthew S. K. Yeo,
  • Charan Satya Chandra Sairam Borusu,
  • M. A. Viraj J. Muthugala,
  • Michael Budig,
  • Mohan Rajesh Elara,
  • Yixiao Wang

DOI
https://doi.org/10.3390/buildings14041110
Journal volume & issue
Vol. 14, no. 4
p. 1110

Abstract

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Mobile service robots employ vision systems to discern objects in their workspaces for navigation or object detection. The lighting conditions of the surroundings affect a robot’s ability to discern and navigate in its work environment. Robot inclusivity principles can be used to determine the suitability of a site’s lighting condition for robot performance. This paper proposes a novel framework for autonomously auditing the Robot Inclusivity Index of indoor environments based on the lighting condition (RII-lux). The framework considers the factors of light intensity and the presence of glare to define the RII-Lux of a particular location in an environment. The auditing framework is implemented on a robot to autonomously generate a heatmap visually representing the variation in RII-Lux of an environment. The applicability of the proposed framework for generating true-to-life RII-Lux heatmaps has been validated through experimental results.

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