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

Author:

Zeng Zimou1ORCID,Yeo Matthew S. K.1ORCID,Borusu Charan Satya Chandra Sairam1ORCID,Muthugala M. A. Viraj J.1ORCID,Budig Michael1ORCID,Elara Mohan Rajesh1ORCID,Wang Yixiao2

Affiliation:

1. Engineering Product Development Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore

2. School of Industrial Design, Georgia Institute of Technology, Atlanta, GA 30332, USA

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.

Funder

National Robotics Programme (NRP) BAU, Ermine III

A*STAR

Publisher

MDPI AG

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