Keith Yu Kit Leung
Papers
7
Total Citations
72
H-Index
5
About
Keith Yu Kit Leung is a leading researcher in mobile robotics, specializing in simultaneous localization and mapping (SLAM) and multi-object estimation. His work has fundamentally advanced how robots perceive and navigate unknown environments, particularly through the innovative application of random finite set (RFS) theory to the SLAM problem. Leung’s major contributions include developing novel metrics for evaluating mapping performance—such as the Cardinalized Optimal Linear Assignment (COLA) metric—which provide principled ways to assess estimation error in both robotic mapping and target tracking. His highly cited paper on metrics for feature-based mapping (25 citations) has become a foundational reference in the field. Leung also pioneered improved weighting strategies for Rao-Blackwellized Probability Hypothesis Density SLAM, enabling more robust data association and detection statistics without heuristic methods. His work on cooperative SLAM in sparsely-communicating robot networks addresses critical challenges in multi-robot systems. With over 70 total citations across his most influential papers, Leung’s research bridges theoretical rigor and practical deployment, making him a key figure in advancing autonomous navigation and multi-object state estimation.
Research Focus
Key Achievements
Top Papers
- 1Metrics for Evaluating Feature-Based Mapping Performance25 citations · 2016
- 2
- 3Generalizing random-vector SLAM with random finite sets10 citations · 2015
- 4
- 5
- 6
- 7