Maopeng Ran
Papers
3
Total Citations
53
H-Index
3
About
Maopeng Ran is a leading researcher in intelligent robotics, with a focus on autonomous navigation, multi-robot coordination, and secure control systems. His work bridges deep reinforcement learning and swarm robotics to address real-world challenges in dynamic and adversarial environments. Ran’s most-cited paper (2021, 27 citations) introduces a behavior-based mobile robot navigation method using deep reinforcement learning, enabling single- and multi-agent systems to navigate without pre-existing maps while avoiding collisions. He further advances the field with a 2024 study (13 citations) on distributed adaptive secure formation control for mobile robots under denial-of-service (DoS) attacks, where only partial access to reference trajectories is available—a critical contribution to resilient multi-robot operations. Earlier, Ran developed an improved particle swarm optimization approach for path planning of an amphibious mouse robot (2011, 13 citations), accounting for liquid dynamics beyond traditional path length metrics. His work has significant implications for autonomous systems in defense, search-and-rescue, and environmental monitoring. With a growing citation record and innovative solutions to security and coordination challenges, Ran is shaping the future of intelligent, secure multi-robot systems.
Research Focus
Key Achievements
Top Papers
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