Hu Fang

Papers

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About

Hu Fang is a robotics researcher whose work centers on the control and navigation of omnidirectional mobile robots (OMRs). Their key contribution lies in integrating model predictive control (MPC) with potential field path planning to enable precise, flexible movement for OMRs—vehicles capable of moving in any direction without turning. In their most-cited paper (11 citations), Fang demonstrates how MPC can be used to follow a path generated by the potential field method, while controlling three independent stepper motors to achieve smooth, collision-free navigation. This work addresses a fundamental challenge in mobile robotics: balancing real-time trajectory tracking with obstacle avoidance. Though early in their career, Fang’s research has already been recognized for its practical approach to improving robot autonomy in constrained environments. Their findings are particularly relevant for applications in warehouse logistics, service robotics, and automated manufacturing, where omni-directional mobility and precise control are critical. As the field moves toward more adaptive and intelligent systems, Fang’s contributions provide a solid foundation for future advances in robot path planning and control.