Stephen McKeague
Papers
2
Total Citations
11
H-Index
2
About
Stephen McKeague is a robotics researcher whose work focuses on enabling seamless human-robot interaction in dynamic, crowded environments. His key research areas include sensor fusion, hand and body tracking, and mobile robot navigation. McKeague’s major contributions lie in developing robust methods for associating hand and body movements with robot perception in real-world settings, addressing the challenge of tracking humans without relying on static cameras or restrictive pose constraints. His most-cited paper, "Hand and body association in crowded environments for human-robot interaction" (2013, 7 citations), proposes a framework for mobile robots to track and interact with people in cluttered spaces. Another notable work, "An Asynchronous RGB-D Sensor Fusion Framework Using Monte-Carlo Methods for Hand Tracking on a Mobile Robot in Crowded Environments" (2013, 4 citations), introduces a probabilistic approach to combine RGB-D data for reliable hand tracking despite sensor asynchrony. While his citation counts reflect early-stage impact, McKeague’s work lays foundational techniques for autonomous robots to navigate and collaborate with humans in unstructured settings, making him a notable contributor to the field of human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 2