Max Robotics — Global Service Robot Directory + US Certification

About

Chi-Chih Hung is a leading researcher in intelligent robotic control systems, with a focus on autonomous mobile robots, manipulator trajectory planning, and collision-free formation control. His work bridges advanced machine learning and real-time robotic applications, particularly through innovative use of actor-critic learning, broad learning systems, and fuzzy neural networks. Hung’s most-cited paper, “Trajectory planning and control of a 7-DOF robotic manipulator” (2014, 10 citations), introduced a biological inverse kinematics method and trajectory tracking approach for redundant manipulators, laying groundwork for dexterous robotic motion. His recent contributions include an intelligent actor-critic learning control for collision-free tracking of Mecanum-wheeled mobile robots (2024, 7 citations) and a novel output recurrent broad learning strategy for formation control of ball-riding robots in industrial cyber-physical systems (2024, 4 citations). Hung also developed a fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels (2024, 2 citations). His work is notable for integrating cyber-physical systems with adaptive learning, advancing safety and efficiency in industrial robotics. With a growing citation impact, Hung’s research is shaping next-generation autonomous systems.