Papers

2

Total Citations

59

H-Index

2

About

Dr. Shufan Wu is a pioneering researcher in robotics and autonomous systems, with a primary focus on space exploration and multi-agent coordination. His work bridges the critical gap between theoretical control systems and practical deployment in high-risk environments. Notably, his most cited paper, "A Multi-agent Reinforcement Learning Method for Swarm Robots in Space Collaborative Exploration" (2020, 40 citations), introduces a groundbreaking framework for using reinforcement learning to enable swarm robots to autonomously collaborate in deep-space missions. This research directly addresses the challenge of mission failure due to single-point faults, offering robust, decentralized solutions that enhance resilience and efficiency. Earlier, Dr. Wu contributed foundational work in mobile robotics with "Path guidance and control of a guided wheeled mobile robot" (2001, 19 citations), which established key principles for precise navigation and control. His contributions are particularly impactful for students and researchers interested in the intersection of artificial intelligence, robotics, and space technology, demonstrating how multi-agent systems can revolutionize exploration in uncertain and hostile environments.

Research Focus

Key Achievements

2
H-Index
2
Papers
59
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
A Multi-agent Reinforcement Learning Method for Swarm Robots in Space Collaborative Exploration
40 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Shanghai Jiao Tong University, Nanjing University of Aeronautics and Astronautics

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago