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About

Junho Yang is a robotics researcher whose work centers on vision-based localization and mapping for autonomous systems operating in challenging, GPS-denied environments. His major contributions lie in developing algorithms that enable unmanned aerial vehicles (UAVs) and ground robots to navigate using only visual and inertial data. Yang’s most cited paper (38 citations) introduces a vision-based localization and mapping method for UAVs in riverine environments, estimating 3D feature positions and vehicle pose without GPS. He further advanced this work by incorporating inertial measurements and exploiting river reflections for improved accuracy (9 citations). For ground robotics, Yang designed a two-phase teaching-and-mowing system for autonomous lawnmowers, using visual landmarks to define boundaries (13 citations), and later developed an omnidirectional-vision system to detect containment within permitted areas (11 citations). His research is notable for addressing real-world constraints like GPS denial and environmental reflections, making his work highly relevant for field robotics. With a total of over 70 citations across his key papers, Yang’s contributions continue to influence the development of robust, vision-based navigation for autonomous vehicles.