Papers

4

Total Citations

16

H-Index

3

About

Kang Ding is a rising researcher in swarm robotics and autonomous navigation, whose work addresses critical challenges in scalability, safety, and computational efficiency for multi-agent systems. His key research areas include motion planning for large-scale robotic swarms, risk-aware decision-making, and navigation frameworks for novel sensor technologies. Ding's major contributions include the development of SwarmPRM, a probabilistic roadmap approach that enables scalable motion planning for swarms of cooperative agents, and SwarmDiff, a generative framework using diffusion transformers for trajectory planning in cluttered environments. His risk-aware non-myopic planner, which employs Conditional Value-at-Risk (CVaR) constraints, represents a significant advance in ensuring safety guarantees for swarm operations. With over 16 citations across his most-cited works published between 2023 and 2025, Ding's research is gaining rapid recognition. Notably, his work on navigation frameworks for solid-state LiDARs addresses a practical gap in mobile robotics, demonstrating his ability to bridge theoretical innovation with real-world applicability. As a researcher whose publications span top venues, Ding is establishing himself as a leading voice in the next generation of swarm intelligence and autonomous systems.

Research Focus

Key Achievements

3
H-Index
4
Papers
16
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
SwarmPRM: Probabilistic Roadmap Motion Planning for Large-Scale Swarm Robotic Systems
6 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Peking University, Robotics Research (United States), Guangdong University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago