Dapeng Yan

Papers

Total Citations

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About

Dapeng Yan is a leading researcher at the intersection of robotics, artificial intelligence, and multi-agent systems, with a focus on enhancing autonomous decision-making in complex environments. His most impactful work, "Graph-Based Knowledge Acquisition With Convolutional Networks for Distribution Network Patrol Robots" (2021, 18 citations), pioneers the use of graph convolutional networks to enrich robotic knowledge in smart grid scenarios, enabling patrol robots to intelligently inspect equipment states. This contribution addresses a critical need in modern energy infrastructure. Yan further advances the field with "Neural observer-based fixed-time formation control of multiagent systems" (2024, 8 citations), introducing robust control strategies for coordinated robot teams. His innovative exploration of robotic olfaction, detailed in "Fuzzy Linguistic Odor Cognition for Robotics Olfaction" (2018, 5 citations), bridges human linguistic reasoning and machine perception, allowing robots to interpret environmental odors through fuzzy logic. With a cumulative citation count exceeding 30, Yan’s work demonstrates significant impact in both theoretical control systems and applied robotics. His research not only pushes boundaries in knowledge acquisition and formation control but also opens new avenues for human-robot interaction through sensory cognition.