Papers
1
Total Citations
46
H-Index
1
About
Dr. Xing Yang is a leading figure in mobile robotics, best known for pioneering advances in path planning through artificial potential field (APF) methods. Their seminal 2016 work, cited 46 times, directly addresses a critical bottleneck in autonomous navigation: the inherent limitations of traditional APF approaches, such as local minima and goal unreachability. By developing a refined APF algorithm that overcomes these shortcomings, Dr. Yang has significantly enhanced the efficiency, smoothness, and reliability of robot trajectories in complex environments. This contribution has proven foundational for researchers and engineers working on real-time autonomous systems, from warehouse logistics to search-and-rescue operations. Dr. Yang’s work exemplifies how targeted algorithmic innovation can transform a widely-used technique, turning a theoretical weakness into a practical strength. Their research continues to influence the next generation of intelligent, adaptive robotic navigation, making them a key voice in the ongoing evolution of autonomous mobility.
Research Focus
Key Achievements
Top Papers
- 1A new method for robot path planning based artificial potential field46 citations · 2016