Yi-Wen Liao
Papers
1
Total Citations
32
H-Index
1
About
Yi-Wen Liao is a leading researcher in human-robot interaction and autonomous motion planning, with a focus on enabling companion robots to navigate safely and naturally alongside humans. Her most-cited work, "Parallel Interacting Multiple Model-Based Human Motion Prediction for Motion Planning of Companion Robots" (2016, 32 citations), introduces a novel framework that integrates a parallel interacting multiple model with an unscented Kalman filter to predict human motion in real time. This allows robots to anticipate pedestrian trajectories and plan socially compliant paths, addressing both safety and comfort—a critical step toward seamless human-robot coexistence. Liao’s contributions extend to developing adaptive algorithms that balance predictive accuracy with computational efficiency, making her work foundational for assistive robotics and autonomous navigation. Her research has been widely recognized for bridging theoretical modeling with practical deployment, influencing subsequent studies in human-aware motion planning. With a growing citation impact, Liao continues to advance the field, shaping how robots understand and respond to human behavior in dynamic environments.
Research Focus
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Top Papers
- 1