Brian Peasley

Clemson University, Microsoft Research (United Kingdom)

Papers

Total Citations

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About

Brian Peasley is a leading researcher in robotics and autonomous navigation, specializing in 3D perception, obstacle detection, and mapping for indoor environments. His work focuses on making low-cost sensors, such as the Microsoft Kinect, reliable for real-world navigation tasks. Peasley’s most cited paper (31 citations) introduces a novel method for real-time obstacle detection and avoidance using active 3D sensors, specifically addressing the challenge of specular surfaces by projecting 3D points onto the ground plane rather than relying on traditional UV-disparity techniques. His 2012 work on accurate on-line 3D occupancy grids (19 citations) achieves nearly drift-free mapping of large indoor spaces by combining odometry with visual registration under a Manhattan world constraint, significantly improving spatial consistency. In a 2015 study (16 citations), Peasley demonstrates that the inexpensive Microsoft Kinect can be used for reliable navigation in large indoor environments, overcoming its high noise levels through innovative processing. These contributions have advanced practical, cost-effective solutions for autonomous robots, making Peasley a notable figure in the field of mobile robotics and sensor-based navigation.