Papers
13
Total Citations
407
H-Index
9
About
Ba-Ngu Vo is a prominent researcher whose work sits at the intersection of autonomous robotics, probabilistic estimation, and multitarget tracking. He is best known for pioneering the application of **Random Finite Set (RFS)** theory to simultaneous localization and mapping (SLAM), fundamentally reshaping how robotic systems represent and reason about uncertain environments. His seminal contributions reframe the SLAM problem using rigorous Bayesian mathematics, enabling more principled treatment of map uncertainty, feature detection, and vehicle localization — areas documented across his most influential publications, including "SLAM Gets a PHD" (71 citations) and his foundational RFS-based SLAM formulations. Vo's research extends into radar-based robotic navigation, sensor scheduling, and collaborative multi-vehicle SLAM, demonstrating both theoretical depth and practical applicability. His 2012 book on robotic radar navigation stands as a key resource for engineers working on real-world autonomous systems. With contributions to multitarget tracking spanning over a decade — including an introductory overview piece that contextualizes the field's 50-year history — Vo has helped bridge classical tracking theory with modern robotic applications. His cumulative citation record reflects sustained influence across robotics, signal processing, and autonomous systems research communities worldwide.
Research Focus
Key Achievements
Top Papers
- 1SLAM Gets a PHD: New Concepts in Map Estimation71 citations · 2014
- 2Robotic Navigation and Mapping with Radar64 citations · 2012
- 3Random Finite Sets for Robot Mapping and SLAM59 citations · 2011
- 4
- 5A random set formulation for Bayesian SLAM47 citations · 2008
- 6Collaborative Multi-vehicle SLAM with moving object tracking34 citations · 2013
- 7Introduction to the issue on multitarget tracking30 citations · 2013
- 8
- 9A hierarchical approach to the Multi-Vehicle SLAM problem15 citations · 2012
- 10