Defu Zhang

Papers

Total Citations

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About

Defu Zhang is a leading researcher in robotics and motion planning, with key contributions spanning asymptotically optimal algorithms and sensor design for biomimetic systems. His most cited work, "Informed Anytime Fast Marching Tree for Asymptotically Optimal Motion Planning" (2020, 29 citations), introduces IAFMT—a groundbreaking sampling-based planner that delivers high-quality solutions in high-dimensional, complex environments. This algorithm advances the field by enabling anytime, asymptotically optimal performance, making it invaluable for real-time robotic applications where solution quality and computational efficiency are critical. Zhang also demonstrates expertise in hardware innovation with "A Highly Reliable Embedded Optical Torque Sensor Based on Flexure Spring" (2018, 12 citations), where he developed a lightweight, highly reliable torque sensor for biomimetic robot arms. By integrating a flexure spring to detect joint torsion, this work enhances the precision and durability of torque measurement in robotic joints, supporting safer and more responsive human-robot interaction. Together, these contributions highlight Zhang’s dual impact on both algorithmic motion planning and embedded sensing, establishing him as a versatile innovator in modern robotics.