Yuancheng Su
Papers
1
Total Citations
131
H-Index
1
About
Yuancheng Su is a leading researcher in mobile robotics and intelligent control systems, with a primary focus on path planning and autonomous navigation. His most influential work, "The Path Planning of Mobile Robot by Neural Networks and Hierarchical Reinforcement Learning" (2020, 131 citations), addresses critical limitations in existing mobile robots, including slow convergence, lack of autonomous learning, and unsmooth planned paths. By integrating neural networks with hierarchical reinforcement learning, Su developed a framework that enables robots to perceive their environment more effectively and generate smoother, more efficient trajectories. This contribution has been widely recognized for advancing the practical deployment of autonomous robots in complex, dynamic settings. Su’s research bridges the gap between theoretical reinforcement learning algorithms and real-world robotic applications, offering scalable solutions for industries ranging from logistics to service robotics. His work continues to influence the development of adaptive, self-improving robotic systems, making him a key figure in the evolution of intelligent autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1