Licheng Wen

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About

Licheng Wen is a leading researcher in multi-agent robotics, with a primary focus on multi-agent path finding (MAPF) and coordinated motion planning. His most impactful contribution is the development of CL-MAPF, a novel framework that addresses the complex challenge of path planning for car-like robots under both kinematic and spatiotemporal constraints. This work, which has garnered 83 citations, provides a critical solution for real-world applications where robots must navigate tight spaces while adhering to realistic motion limits. Wen has also advanced the field of formation control through his work on decentralized hierarchical learning, enabling multiple agents to move together in a structured formation—a capability with direct implications for mobile warehouse robotics and automated logistics. His practical expertise is underscored by his role in the ZJUNLict team, which won the RoboCup 2018 Small Size League championship, demonstrating his ability to translate theoretical algorithms into winning, real-world robotic systems. By bridging the gap between theoretical MAPF and the physical constraints of real robots, Wen’s research is paving the way for more efficient and coordinated multi-robot teams in industrial and service settings.