Papers

1

Total Citations

4

H-Index

1

About

Dr. BI Yi-fei is a leading researcher in multi-robot systems and autonomous navigation, with a focus on integrating artificial intelligence with robotic decision-making. His most-cited work, "Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization" (2025, 4 citations), addresses a critical challenge in the field: ensuring collision-free movement in decentralized multi-robot systems. Dr. BI's major contribution lies in combining deep reinforcement learning with trajectory optimization techniques to overcome the safety limitations of existing low-cost, decentralized obstacle avoidance strategies. This innovative approach enhances both the safety and efficiency of multi-robot coordination, with significant implications for applications in warehouse logistics, search-and-rescue operations, and autonomous drone swarms. His research bridges the gap between theoretical AI methods and practical robotic systems, offering scalable solutions for real-world deployment. Dr. BI's work is particularly notable for its potential to improve decision-making capabilities in complex, dynamic environments, marking him as an emerging authority in the intersection of reinforcement learning and robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization
4 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Shanghai for Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago