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About

Frazer Noble is a robotics researcher whose work spans depth perception, assistive exoskeletons, and visible light positioning (VLP) for autonomous navigation. His highly cited 2017 paper comparing RGB-D cameras for robotics applications (37 citations) established foundational knowledge on the accuracy and repeatability of consumer-grade depth sensors, directly informing robotic perception system design. That same year, his review of commercially available medical exoskeletons (37 citations) provided a critical, weighted analysis of four market-leading devices—REX, ReWalk, Ekso GT, and Indego—offering a benchmark for assistive robotics. More recently, Noble has pioneered VLP for robot localization, developing an autonomous fingerprinting method that leverages consumer-grade virtual reality hardware to collect large-scale experimental data (15 citations). His 2024 work extends VLP to enable robot navigation using existing indoor lighting infrastructure. Noble’s research uniquely bridges hardware evaluation, assistive technology, and novel sensing paradigms, with his work on RGB-D cameras and exoskeletons remaining essential reading for students and engineers entering these fields.