Yifan Liao

Papers

Total Citations

136

H-Index

About

Yifan Liao is a robotics researcher whose work focuses on intelligent navigation and autonomous inspection systems, with particular emphasis on integrating neural networks and reinforcement learning for mobile robot control. Liao’s most influential contribution, “The Path Planning of Mobile Robot by Neural Networks and Hierarchical Reinforcement Learning” (2020), has garnered 131 citations and addresses critical challenges in autonomous robotics—namely, slow convergence, unsmooth paths, and limited self-learning capabilities. By combining neural perception with hierarchical reinforcement learning, this work enables robots to perceive their environment more effectively and generate smoother, more efficient trajectories. Liao also explores applied robotics in safety-critical domains, as seen in “Research on Fire Inspection Robot Based on Computer Vision” (2021), which investigates how computer vision can enhance fire patrol robots for real-world hazard detection. While still early-stage, this work signals a commitment to translating algorithmic advances into practical, life-saving technologies. Liao’s research sits at the intersection of machine learning, control theory, and field robotics, offering valuable insights for students and engineers working on autonomous navigation, inspection systems, and intelligent robot design.