Lingfeng Pang
Papers
1
Total Citations
23
H-Index
1
About
Dr. Lingfeng Pang is a rising researcher in mobile robotics, with a primary focus on intelligent path planning and autonomous navigation. His most cited work introduces a novel "Predator-Prey Reward Based Q-Learning Coverage Path Planning" algorithm, which addresses the fundamental challenge of Coverage Path Planning (CPP) for mobile robots. By integrating reinforcement learning principles with bio-inspired predator-prey dynamics, Dr. Pang’s approach significantly improves the efficiency and adaptability of robot coverage in complex environments. This paper, published in 2023, has already garnered 23 citations, reflecting its timely impact on the field. His contributions lie at the intersection of machine learning and robotic control, offering practical solutions for applications ranging from automated cleaning to agricultural surveying. Dr. Pang’s work is notable for advancing Q-learning-based CPP algorithms, a relatively underexplored area, and for demonstrating how reward structures can be optimized to mimic natural behaviors. As a developing scholar, his research promises to shape future autonomous systems, making him a name to watch in intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1