Mu‐Chun Su

Papers

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About

Mu-Chun Su is a leading researcher in intelligent robotics and human–machine interaction, with a particular focus on gesture-based control and adaptive navigation systems. His pioneering work on hand-gesture interfaces for robotic platforms, exemplified by his highly cited 2010 paper (48 citations), introduced a practical method using a 3-axis accelerometer and wireless RF transmission to classify hand trajectories for real-time car-robot control—a foundational contribution to intuitive, non-contact robotic operation. In parallel, Su advanced autonomous navigation through his 2004 reinforcement-learning approach (14 citations), which enabled mobile robots to incrementally adapt to unknown environments by constructing fuzzy rules from sensory inputs. This work demonstrated how robots could learn optimal behaviors through trial and error, bridging reinforcement learning with fuzzy logic for robust, goal-directed navigation. Su’s research has significantly influenced the development of user-friendly robotic interfaces and self-adaptive systems, with his gesture-control work remaining a key reference for applications in assistive technology and autonomous vehicles. His contributions continue to inspire new generations of researchers exploring the intersection of machine learning, sensor fusion, and human–robot collaboration.