Zeng
Papers
2
Total Citations
8
H-Index
2
About
Zeng’s research focuses on the intersection of robotics, precision manufacturing, and intelligent control systems, with particular emphasis on humanoid robot locomotion and automated assembly processes. Their most cited work, “Gait control of humanoid robots via fuzzy logic and iterative optimization” (2011, 5 citations), introduced a novel approach to stabilizing bipedal walking by combining fuzzy logic with iterative learning, enabling more adaptive and energy-efficient gait patterns. This contribution laid groundwork for more robust humanoid motion in unstructured environments. In a second highly cited paper (2013, 3 citations), Zeng addressed a critical challenge in aircraft assembly: real-time normal vector detection and auto-normalization for robotic drilling systems. They developed a multi-sensor perception system using four laser displacement sensors mounted on the end-effector to measure deviations between the spindle axis and the workpiece surface. Through an inverse kinematics-based auto-normalization algorithm, the robot could autonomously adjust its pitch and yaw around the tool center point, correcting alignment errors to within 0.5 degrees. Experimental validation using a laser tracker confirmed the system’s precision, significantly improving drilling accuracy in aerospace manufacturing. Though citation counts are modest, Zeng’s work demonstrates practical engineering impact—bridging theoretical control methods with real-world industrial automation—and has influenced subsequent research in both humanoid robotics and intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
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