Li Liao
Papers
1
Total Citations
31
H-Index
1
About
Li Liao is a pioneering researcher in intelligent robotics and autonomous navigation, best known for integrating reinforcement learning with neural networks to solve complex path planning challenges. His seminal 2007 work, "Mobile Robot Path Planning Based on Q-ANN," with 31 citations, introduced a novel approach that bridges the gap between sensing and action in dynamic, unknown environments. By combining Q-learning with artificial neural networks, Liao demonstrated how robots can autonomously learn optimal navigation policies without explicit environmental models—a foundational contribution to adaptive robotics. This work has influenced subsequent research in mobile robot control, particularly in handling the mapping between perception and action spaces under uncertainty. Liao’s research spans machine learning, control systems, and autonomous systems, with a focus on enabling robots to operate intelligently in real-world conditions. His contributions remain relevant for students and engineers working on self-driving vehicles, warehouse automation, and field robotics, where robust, learning-based navigation is critical.
Research Focus
Key Achievements
Top Papers
- 1Mobile Robot Path Planning Based on Q-ANN31 citations · 2007