David Tick
Papers
6
Total Citations
107
H-Index
5
About
David Tick is a robotics researcher whose work sits at the intersection of autonomous navigation, computer vision, and sensor fusion. His most significant contributions center on developing robust localization systems for mobile robots, particularly through his innovative use of both discrete and continuous epipolar geometry — a vision-based approach that extracts position, orientation, and velocity data from image sequences using Euclidean homography matrices. His most-cited work, "Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry" (2012, 35 citations), exemplifies his hallmark methodology: integrating visual odometry with inertial measurement units and wheel odometry to achieve highly accurate real-world robot localization. A series of related papers from 2010 to 2013 traces the evolution of this "chained fusion" framework from concept to full navigation and path-following systems. Beyond localization, Tick has also contributed to terrain classification, proposing a vibration-based hierarchical approach enabling robots to categorize surfaces simply by traversing them. With over 100 cumulative citations, his research has meaningfully advanced the practical autonomy of wheeled mobile robots operating in complex indoor environments.
Research Focus
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Top Papers
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