Ya-Fang Ho
Papers
3
Total Citations
52
H-Index
3
About
Ya-Fang Ho is a robotics researcher whose work bridges bio-inspired computation, intelligent control, and humanoid locomotion. Her key research areas include swarm intelligence, obstacle avoidance, and robotic manipulation. Ho’s most cited work introduces a “migrant-inspired” path planning algorithm that fuses particle swarm optimization (PSO) with potential field navigation and fuzzy logic—a novel approach that mimics animal migration to help robots navigate cluttered environments (23 citations). She further advanced PSO by developing adaptive inertia weight and acceleration coefficients, enabling a robotic arm to grasp and place water-filled bottles without spilling (18 citations). In humanoid robotics, Ho proposed a parameterized gait pattern generator based on the linear inverted pendulum model, using natural ZMP references to produce stable, adjustable walking gaits (11 citations). Her contributions are notable for integrating biologically inspired heuristics with practical control challenges, offering scalable solutions for real-world robotics. With a growing citation footprint, Ho’s work is increasingly referenced in studies on autonomous navigation, dexterous manipulation, and bipedal locomotion—making her a rising voice in intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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