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

10
H-Index
14
Papers
927
Total Citations
66
Avg Citations/Paper
🏆 Most Cited Paper
The bridge test for sampling narrow passages with probabilistic roadmap planners
358 citations · 2004
📈 Most Prolific Year: 2004 (4 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Duke University, Hong Kong Baptist University, Google (United States), Xi'an Jiaotong University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago