Papers
1
Total Citations
4
H-Index
1
About
Yunsen Duan is a researcher advancing the frontier of intelligent robotics and autonomous systems, with a primary focus on reinforcement learning, multi-agent path planning, and warehouse automation. His most cited work, "Deep Reinforcement Learning-based Multi-AMR Path Planning Algorithm" (2023), tackles the critical challenge of scheduling multiple autonomous mobile robots (AMRs) in box storage environments. By identifying the inefficiencies of traditional dynamic programming methods, Duan pioneered a reinforcement learning framework that significantly improves feasible path computation, offering a scalable and adaptive solution for real-world logistics. Though early in its impact trajectory with 4 citations, this work signals a promising contribution to industrial robotics and smart warehousing. Duan’s research bridges the gap between theoretical reinforcement learning algorithms and practical deployment, addressing the growing demand for efficient, collision-free multi-robot coordination. His work holds particular relevance for students and engineers exploring deep RL applications in automation, and positions him as an emerging voice in the optimization of autonomous material handling systems.
Research Focus
Key Achievements
Top Papers
- 1Deep Reinforcement Learning-based Multi-AMR Path Planning Algorithm4 citations · 2023