Ming‐Li Chiang
Papers
3
Total Citations
20
H-Index
2
About
Ming-Li Chiang is a robotics researcher whose work bridges autonomous navigation, human-robot interaction, and rehabilitation engineering. Her key research areas include social robotics, assistive exoskeletons, and machine learning for real-time control systems. In her most cited work, Chiang introduced the multi-layer environmental affordance map, a novel architecture enabling service robots to integrate perception and inference for socially friendly navigation and event detection—a contribution that has garnered 10 citations and laid groundwork for context-aware indoor robotics. She further advanced rehabilitation technology with a velocity field-based active-assistive control method for upper limb exoskeletons, addressing critical limitations of conventional time-dependent trajectory approaches and enabling multi-joint task-based therapy (8 citations). Chiang also developed a supervised recurrent neural network for real-time obstacle avoidance, featuring automatic data collection and labeling to streamline deployment (2 citations). Her work is notable for its practical focus on real-world implementation, from social companion robots to clinical rehabilitation devices. With a growing citation record and contributions that directly impact how robots perceive environments and assist humans, Chiang is establishing herself as a rising voice in intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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