Jianfeng Zheng
Papers
1
Total Citations
32
H-Index
1
About
Jianfeng Zheng is a leading researcher in robotics and artificial intelligence, with a primary focus on autonomous navigation and deep reinforcement learning. His most influential work, "Improved Path Planning for Indoor Patrol Robot Based on Deep Reinforcement Learning" (2022, 32 citations), addresses critical challenges in robotic exploration and convergence speed. Zheng proposed a novel algorithm that integrates Pan/Tilt/Zoom (PTZ) image information to enhance the navigation performance of patrol robots along indoor specified routes. This contribution has significantly advanced the practical deployment of intelligent robots in security and surveillance applications. By combining computer vision with reinforcement learning, Zheng's approach improves both the efficiency and reliability of autonomous path planning. His work is widely recognized for bridging the gap between theoretical reinforcement learning algorithms and real-world robotic systems, making him a notable figure in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1