Peigang Li
Papers
1
Total Citations
2
H-Index
1
About
Peigang Li is a robotics researcher whose work centers on intelligent path planning and obstacle avoidance for mobile robots. His most cited contribution, published in 2025, introduces a dynamically hybrid algorithm that fuses an improved A-star search with the dynamic windows approach. This method significantly enhances real-time navigation in complex environments, allowing robots to efficiently compute global paths while seamlessly adapting to dynamic obstacles. Li’s algorithm reduces computational overhead and improves safety margins, addressing a critical bottleneck in autonomous mobile systems. With 2 citations already, this work is gaining traction among researchers in robotics and automation. Li’s achievement lies in bridging the gap between global planning and local reactive control—a challenge that has long limited practical deployment of mobile robots. His approach is particularly notable for its balance of optimality and real-time performance, making it suitable for applications in warehouse logistics, service robotics, and autonomous vehicles. As a rising scholar, Li is contributing to the next generation of adaptive navigation systems, promising safer and more efficient autonomous movement in unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1