Feiyu Hu

Papers

Total Citations

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About

Feiyu Hu is a robotics researcher whose work centers on autonomous navigation and deformable object manipulation, with a particular focus on solving real-world challenges in unstructured and dynamic environments. His most-cited paper, "Optimized motion planning for mobile robots in dynamic construction environments with low-feature mapping and pose-based positioning" (2025, 7 citations), introduces a novel approach to robot navigation in complex, feature-sparse construction sites. By integrating low-feature mapping with pose-based positioning, Hu’s method enables mobile robots to maintain robust localization and plan efficient paths despite the clutter and unpredictability typical of construction settings—a critical step toward practical deployment of autonomous systems in the building industry. Hu’s work on deformable linear objects (DLOs) further demonstrates his innovative approach to robotic manipulation. In "Rearranging Deformable Linear Objects for Implicit Goals with Self‐Supervised Planning and Control" (2024, 2 citations), he tackles the notoriously difficult problem of manipulating cables, ropes, and hoses without explicit goal definitions. By developing a self-supervised framework that learns to rearrange DLOs while respecting physical constraints, Hu opens new possibilities for automation in manufacturing, wiring, and surgical robotics. His research bridges the gap between theoretical planning and practical constraint-aware control, earning recognition for addressing a frontier problem in robotics. With a growing citation impact, Hu is establishing himself as a rising voice in intelligent autonomous systems.