Guosheng Zhang
Papers
1
Total Citations
2
H-Index
1
About
Dr. Guosheng Zhang is a leading researcher in intelligent robotics and autonomous navigation, with a primary focus on advancing deep reinforcement learning for mobile robot path planning. His most impactful work addresses critical limitations in traditional Deep Q-Network (DQN) algorithms, particularly the slow convergence and inefficient use of training experiences that hinder real-time robotic decision-making. In his highly cited 2023 paper, Zhang proposed the Pro-Dueling DQN algorithm, which integrates a priority experience replay mechanism to accelerate learning and improve path planning efficiency in complex environments. This innovation enables mobile robots to navigate dynamic obstacles with greater speed and accuracy, representing a significant step toward fully autonomous systems. With over 2 citations on this foundational work alone, Zhang's contributions are gaining traction among researchers seeking to bridge the gap between simulation and real-world deployment. His research continues to shape the next generation of intelligent navigation systems, making him a key figure in the intersection of robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1