Papers
13
Total Citations
290
H-Index
10
About
David Kent is a robotics researcher whose work sits at the intersection of human-robot interaction, remote teleoperation, and robot learning. He has made significant contributions to how humans communicate with and teach robots, particularly in the context of object manipulation and task execution. His most influential work examines teleoperation interfaces for high-degree-of-freedom robot manipulators, with papers on remote control interfaces accumulating over 100 citations combined, demonstrating the field's strong interest in making robot control more accessible and effective. Kent is also a pioneer in applying crowdsourcing methodologies to robotics research — his Robot Management System framework, cited over 90 times across versions, established a novel approach for conducting large-scale human-robot interaction studies without traditional laboratory constraints. His crowdsourcing work extended to building 3D object recognition databases for robotic grasping, reducing the resource burden of training data collection. More recently, Kent has tackled adaptive human-robot collaboration through his UHTP framework, enabling robots and humans to fluidly share task responsibilities without explicit communication. Across his career, Kent's research consistently pursues a unifying goal: making robots more capable partners for non-expert human users in real-world environments.
Research Focus
Key Achievements
Top Papers
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- 6Towards Robot Adaptability in New Situations.14 citations · 2015
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- 10Construction of an object manipulation database from grasp demonstrations11 citations · 2014