Ke-Hao Chang

National Taiwan University, Southern Taiwan University of Science and Technology

Papers

Total Citations

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About

Ke-Hao Chang is a robotics researcher whose work focuses on the intersection of intelligent control systems and bipedal locomotion. His primary research areas include adaptive neuro-fuzzy inference systems (ANFIS), artificial neural networks, and gait balance control for humanoid robots. Chang’s most influential contribution is his 2007 paper, “ANFIS based Controller Design for Biped Robots” (11 citations), which pioneered a novel approach using ANFIS as a system identifier to model biped robot dynamics before deploying a motion controller. This work laid the groundwork for more adaptive and stable walking patterns in humanoid robots. He further advanced the field with his 2007 study on an artificial neural network-based controller for gait balance (5 citations), demonstrating how back-propagation neural networks could enable real-time, online learning for joint corrections during locomotion. Earlier in his career, Chang contributed to multi-robot systems through his 2005 paper on system design for five-on-five robot soccer competitions (3 citations), where he optimized robot mobility by minimizing unnecessary mechanical functions. Collectively, his research has garnered 19 citations, reflecting his role in advancing intelligent control strategies for autonomous robots.