Qihang Peng
Papers
1
Total Citations
13
H-Index
1
About
Dr. Qihang Peng is a leading researcher in multirobot systems and autonomous decision-making, with a core focus on developing efficient search and coordination algorithms for dynamic environments. His most impactful work introduces DRL-Searcher, a unified deep reinforcement learning framework that addresses the challenging problem of multirobot efficient search (MuRES) for a nonadversarial moving target. This contribution, published in 2023 and already garnering 13 citations, fundamentally advances the field by moving beyond traditional optimization approaches—which typically focus on minimizing expected capture time or maximizing capture probability within a time budget—to a more flexible, learning-based paradigm. By enabling robots to adapt their search strategies in real time, Dr. Peng’s research bridges the gap between theoretical search theory and practical multirobot deployment. His work is particularly notable for its potential applications in search-and-rescue, surveillance, and environmental monitoring, where rapid target localization is critical. With a growing citation record and a clear trajectory of innovation, Dr. Peng is establishing himself as a key contributor to the next generation of intelligent, autonomous multiagent systems.
Research Focus
Key Achievements
Top Papers
- 1