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About

Changxiang Fan is a leading researcher in multi-robot cooperative manipulation and human–robot collaboration, with a focus on enabling complex, real-world tasks through intelligent planning and coordination. Their work addresses fundamental challenges in non-prehensile manipulation, where multiple mobile robots must cooperatively lift, support, and transport large objects without grasping them. Fan introduced a modal planning framework that efficiently probes configuration space by defining modes as constraint-based configurations and precomputing transitions, a contribution that has garnered 11 citations and laid groundwork for scalable multi-robot systems. They also developed a three-mobile-robot system for cooperative transportation in narrow spaces, demonstrating practical deployment with 8 citations. In human–robot collaboration, Fan’s 2025 paper on task allocation and scheduling uniquely synergizes efficiency and fatigue reduction, earning 9 citations and highlighting their commitment to human-centered automation. Their earlier work on least action sequence determination further advanced non-prehensile manipulation planning. With a growing citation record and a portfolio bridging theory and application, Fan is shaping the future of autonomous multi-robot systems and collaborative manufacturing.