A Framework for Auditing Robot-Inclusivity of Indoor Environments Based on Lighting Condition
Author(s): |
Zimou Zeng
Matthew S. K. Yeo Charan Satya Chandra Sairam Borusu M. A. Viraj J. Muthugala Michael Budig Mohan Rajesh Elara Yixiao Wang |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 27 March 2024, n. 4, v. 14 |
Page(s): | 1110 |
DOI: | 10.3390/buildings14041110 |
Abstract: |
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. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10773434 - Published on:
29/04/2024 - Last updated on:
05/06/2024