Changhuang Wan

Papers

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About

Changhuang Wan is a robotics researcher whose work centers on motion planning, task allocation, and multi-agent coordination for field robotics. His most cited paper, "Motion Planning and Task Allocation for a Jumping Rover Team" (2020, 7 citations), introduces a novel cooperative framework where unmanned ground vehicles (UGVs) with hybrid operational modes—capable of both ground travel and jumping—solve the multiple traveling salesman problem (mTSP) in obstacle-rich environments. This contribution is significant for enabling agile, cost-effective robotic teams to navigate challenging terrains, with potential applications in planetary exploration, disaster response, and search-and-rescue missions. By integrating task allocation with dynamic motion planning, Wan’s work advances the efficiency and autonomy of multi-robot systems. His research has been recognized for its practical impact, offering a scalable solution for real-world deployment where traditional wheeled or legged robots may struggle. Wan’s findings continue to inspire further studies in cooperative robotics and adaptive locomotion, marking him as an emerging voice in the field of autonomous systems.