Shaoming Peng
Papers
1
Total Citations
2
H-Index
1
About
Shaoming Peng is a leading researcher in multi-robot systems and artificial intelligence, with a focus on path planning and coordination in dynamic environments. His most-cited work, "Multi-Robot Path Planning Combining Heuristics and Multi-Agent Reinforcement Learning" (2023), addresses the classic challenge of enabling multiple robots to navigate without collisions while minimizing travel distance. Peng’s key contribution lies in integrating heuristic search methods with multi-agent reinforcement learning, offering a more adaptive and efficient solution than traditional replanning approaches. This work, already garnering 2 citations, demonstrates his ability to bridge theoretical algorithms with practical robotic applications. His research has significant implications for warehouse automation, autonomous fleets, and swarm robotics, where real-time collision avoidance is critical. Peng’s innovative fusion of heuristics and learning continues to influence the field, making him a notable figure in advancing intelligent, cooperative multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1