Autor: |
Zimou Zeng, Matthew S. K. Yeo, Charan Satya Chandra Sairam Borusu, M. A. Viraj J. Muthugala, Michael Budig, Mohan Rajesh Elara, Yixiao Wang |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Buildings, Vol 14, Iss 4, p 1110 (2024) |
Druh dokumentu: |
article |
ISSN: |
2075-5309 |
DOI: |
10.3390/buildings14041110 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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