Papers
14
Total Citations
927
H-Index
10
About
Zheng Sun is a leading researcher in robotic motion planning, whose work has fundamentally advanced the field of probabilistic roadmap (PRM) planners. His primary research areas include sampling strategies for narrow passages in configuration spaces, optimal path planning on complex terrains, and energy-efficient robotic navigation. Sun's most influential contribution is the development of the "bridge test" for sampling narrow passages, a landmark paper with 358 citations that introduced a hybrid sampling strategy to overcome one of the most persistent challenges in PRM planning. This work, along with his subsequent papers on narrow passage sampling (173 citations) and cost-sensitive adaptive strategies (111 citations), established a systematic framework for addressing the narrow passage problem. Sun also made significant contributions to energy-minimizing path planning on terrains, where he modeled the physical costs of friction and gravity for mobile robots. His research on frictional mechanical systems explored the computational power of mechanical linkages, demonstrating remarkable breadth. With over 900 total citations across his most-cited works, Sun's research continues to influence both theoretical foundations and practical applications in robotic path planning.
Research Focus
Key Achievements
Top Papers
- 1The bridge test for sampling narrow passages with probabilistic roadmap planners358 citations · 2004
- 2Narrow passage sampling for probabilistic roadmap planning173 citations · 2005
- 3Hybrid PRM Sampling with a Cost-Sensitive Adaptive Strategy111 citations · 2006
- 4On finding energy-minimizing paths on terrains83 citations · 2005
- 5On finding approximate optimal paths in weighted regions62 citations · 2004
- 6On energy-minimizing paths on terrains for a mobile robot47 citations · 2004
- 7Movement Planning in the Presence of Flows30 citations · 2004
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- 10On Frictional Mechanical Systems and Their Computational Power11 citations · 2003