Ming-Feng Lu

Papers

Total Citations

H-Index

About

Ming-Feng Lu is a robotics researcher whose work centers on humanoid robot locomotion, autonomous control, and vision-based systems. His major contributions lie in developing control strategies that enable humanoid robots to perform complex, real-world tasks. In his most cited work (2007, 17 citations), Lu introduced a fuzzy-based auto-balance gait controller using force and accelerometer sensors, allowing a humanoid robot to autonomously climb stairs by leveraging the Zero Moment Point (ZMP) criterion—a foundational achievement in stable bipedal locomotion. He further advanced the field by integrating omni-directional vision with control strategy for humanoid soccer robots (2007, 5 citations), creating a visual feedback system that combines hardware, servo control, and sensory systems for dynamic environments. Lu also explored embedded system design, implementing a self-balancing weight-lifting controller on an SOPC chip (2008, 3 citations), demonstrating how programmable logic can achieve compact, efficient control for small humanoids. Though his citation counts are modest, Lu’s work is notable for its practical, systems-level approach—bridging sensor fusion, gait planning, and real-time control—making him a contributor to the foundational engineering that underpins modern humanoid robotics.