Bojun Yang

National Yunlin University of Science and Technology

Papers

Total Citations

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About

Bojun Yang is a researcher at the forefront of autonomous mobile robotics, with a primary focus on integrating artificial intelligence and machine learning into robotic control systems. His work centers on developing intelligent navigation and behavior control for mobile robots, particularly in the areas of docking and obstacle avoidance. Yang’s most cited paper, "Applying Reinforcement Learning for AMR’s Docking and Obstacle Avoidance Behavior Control" (2025, 3 citations), demonstrates a novel approach to enabling autonomous mobile robots (AMRs) to learn and execute complex maneuvers through reinforcement learning within the Robot Operating System (ROS) framework. This contribution is pivotal for advancing the practical deployment of robots in industrial and service sectors. Additionally, his earlier work, "Application of the MyRIO Based Mobile Robot Using Vision System" (2020, 2 citations), explores the integration of vision systems for enhanced robotic perception. Yang’s research bridges the gap between theoretical AI advancements and real-world robotic applications, offering scalable solutions for autonomous navigation. His work is particularly valuable for students and researchers interested in reinforcement learning, ROS-based robotics, and the future of intelligent automation.