Fangyi Wan

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About

Fangyi Wan is a rising researcher in robotics and autonomous systems, with a primary focus on motion planning and path optimization. Their most notable contribution is the development of Stack-RRT*, a novel random tree expansion algorithm introduced in their 2023 paper of the same name. This work addresses a critical challenge in robotics—generating smooth, feasible paths for autonomous agents in complex environments—by enhancing the efficiency and quality of sampling-based planning. The algorithm has already garnered 28 citations, signaling its growing influence in the field. Wan’s research bridges theoretical advances in computational geometry with practical applications in mobile robotics and autonomous navigation. By improving upon the classic RRT* framework, they have provided a tool that balances computational speed with path smoothness, a key requirement for real-world deployment. Their work is particularly relevant for students and engineers tackling motion planning in cluttered or dynamic settings. With this early-career achievement, Fangyi Wan is establishing themselves as a thoughtful contributor to the next generation of intelligent robotic systems.