Kang-Hao Liou

National Yunlin University of Science and Technology

Papers

Total Citations

H-Index

About

Kang-Hao Liou is a researcher specializing in robotics and control systems, with a particular focus on reinforcement learning applications for autonomous mobile platforms. His most cited work, "Reinforcement Learning-Based Two-Wheel Robot Control" (2018), has garnered 3 citations, demonstrating his early contributions to integrating machine learning techniques with classical robot control challenges. This research explores how reinforcement learning algorithms can enable two-wheeled robots to achieve stable, adaptive locomotion without explicit programming—a foundational step toward more intelligent, self-learning robotic systems. While his citation count is modest, Liou's work sits at the intersection of control theory and artificial intelligence, addressing practical problems in robot stabilization and path planning. His research is particularly relevant for students and engineers interested in bridging the gap between simulation-based reinforcement learning and real-world robotic hardware. As the field of autonomous robotics continues to expand, Liou's contributions provide a valuable case study in applying modern AI methods to traditional control problems, offering insights for those developing next-generation mobile robots capable of learning from their environments.