Feiyang Suo

Papers

Total Citations

H-Index

About

Feiyang Suo is a robotics researcher whose work focuses on advancing path planning algorithms for autonomous systems. His primary research areas include motion planning, sampling-based algorithms, and intelligent navigation in complex environments. Suo’s major contribution is the development of the Bidirectional Homotopy-Guided RRT (Rapidly-exploring Random Tree), a novel approach that addresses a critical limitation of traditional RRT algorithms: their over-reliance on randomness and failure to leverage known map information. By integrating homotopy-guided heuristics and bidirectional tree growth, his method significantly reduces the blindness of tree expansion, enabling more efficient and deterministic path planning in cluttered or obstacle-rich settings. While his most-cited paper has garnered 2 citations to date, the work represents a meaningful step toward making sampling-based planners more practical for real-world robotic applications. Suo’s research is particularly relevant for autonomous vehicles, warehouse robots, and field robotics, where reliable navigation under uncertainty is essential. His contributions highlight the ongoing evolution of RRT-based methods toward greater intelligence and adaptability.