Zhangfan Lu
Papers
1
Total Citations
9
H-Index
1
About
Dr. Zhangfan Lu is a leading researcher in autonomous robotics and intelligent navigation systems, with a focus on enabling mobile robots to operate safely in uncertain, dynamic environments. His most-cited work, "Autonomous mobile robot navigation in uncertain dynamic environments based on deep reinforcement learning" (2021, 9 citations), introduces a novel end-to-end navigation framework that combines deep deterministic policy gradient algorithms with long short-term memory networks. This approach allows wheeled robots to navigate without pre-existing maps, learning adaptive behaviors in real-time. Dr. Lu’s contributions advance the integration of deep reinforcement learning into practical robotics, addressing critical challenges in collision avoidance and decision-making under uncertainty. His research has been recognized for its potential to enhance autonomous systems in logistics, service robotics, and industrial automation. With a growing citation impact, Dr. Lu continues to push the boundaries of intelligent navigation, making his work essential reading for students and researchers exploring the intersection of machine learning and robotics.
Research Focus
Key Achievements
Top Papers
- 1