Papers
6
Total Citations
121
H-Index
5
About
Yiduo Wang is a robotics researcher whose work lies at the intersection of autonomous search, active perception, and robotic navigation in complex, real-world environments. His most significant contributions address the challenge of enabling robots to operate intelligently in large-scale, unstructured, or hazardous settings. Wang pioneered the "Entrotaxis-Jump" algorithm, a hybrid search strategy for locating unknown emission sources in road-constrained areas, and developed cognitive search methods for diffusive sources in obstructed environments, directly impacting emergency response in chemical clusters. His research on active mapping, notably the system for quadruped robots to autonomously survey industrial structures using information gain-based planning, has garnered significant attention, with his top-cited paper accumulating 39 citations. Wang has also advanced multi-robot collaborative search strategies and addressed fundamental perception challenges, including 3D LiDAR reconstruction with probabilistic depth completion for safe navigation and the critical role of coordinate frames in dynamic SLAM. Through these contributions, Wang is shaping the future of autonomous systems that can perceive, plan, and act in the dynamic, obstacle-filled world, moving beyond static assumptions to enable truly robust robotic operation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6The Importance of Coordinate Frames in Dynamic SLAM4 citations · 2024