David Jaz Myers

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About

David Jaz Myers is a pioneering researcher at the intersection of tactile sensing and robotic perception. His foundational work in tactile image processing established critical methods for edge detection in robotic touch systems, most notably in his highly cited 2005 paper "Edge detection in tactile images" (40 citations). By adapting well-known computer vision edge detection algorithms to tactile sensing, Myers demonstrated how two-dimensional median filtering with 3×3 windows could effectively remove noise from tactile images, enabling robots to "feel" edges and contours with unprecedented accuracy. His contributions have been instrumental in advancing haptic feedback systems and dexterous manipulation in robotics. Working extensively with the LTS-200 tactile sensor array, Myers developed robust preprocessing techniques that remain standard references in the field. His research bridges the gap between visual and tactile perception, showing how classical image processing methods can be repurposed for touch-based sensing. This work has influenced subsequent developments in robotic grasping, medical palpation devices, and autonomous systems requiring tactile awareness. Myers continues to explore how tactile edge detection can enhance human-robot interaction and sensory substitution systems.