Travis Dick

Papers

Total Citations

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About

Travis Dick is a researcher whose work sits at the intersection of human-robot interaction, assistive technology, and computer vision. His key research areas include developing intuitive command interfaces for robots, advancing prosthetic control systems, and creating robust visual tracking algorithms. Dick’s major contributions include the development of SEPO, a natural human-robot command interface using pointing gestures captured by a Kinect sensor—a system designed to make robot control as intuitive as human communication. In the field of prosthetics, he pioneered real-time prediction learning for the simultaneous actuation of multiple prosthetic joints, a technique that promises to significantly enhance the dexterity and usability of multi-joint prostheses for amputees. His work on real-time registration-based tracking introduced a novel algorithm leveraging approximate nearest neighbour search to handle larger per-frame motions than standard methods. With his most-cited papers garnering 38 and 36 citations respectively, Dick’s research has demonstrably influenced the development of more natural and capable robotic and prosthetic systems, bridging the gap between human intent and machine action.