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About

Yonhon Ng is a robotics researcher specializing in bio-inspired vision sensors, visual navigation, and state estimation. His work centers on event cameras—dynamic vision sensors that capture asynchronous intensity changes with exceptional temporal resolution, high dynamic range, and low latency—making them ideal for challenging robotics applications. Ng’s major contributions include developing “Smart Visual Beacons” that combine event cameras with asynchronous optical communication for robust target tracking (18 citations), and a linear comb filter for removing event flicker to improve sensor reliability (17 citations). He also advanced hybrid event-frame camera systems with an asynchronous linear filter architecture that merges the strengths of both sensor types for high dynamic range imaging (11 citations). In visual navigation, Ng proposed a dense optical-flow algorithm with uncertainty estimation for monocular SLAM, enabling robust ego-motion estimation and collision avoidance (6 citations), and explored equivariant systems theory for visual odometry in unstructured environments (6 citations). His earlier work on passive TDoA-based localization using recursive methods laid groundwork for multi-sensor positioning. With over 60 total citations, Ng’s research bridges event-based sensing and classical computer vision, pushing the boundaries of real-time, low-latency perception for autonomous robots.