Xianluo Li
Papers
1
Total Citations
3
H-Index
1
About
Xianluo Li is a researcher specializing in multi-vehicle systems, path planning, and swarm intelligence optimization, with a focus on overcoming real-world navigation challenges. Their major contribution lies in developing a joint grid network and improved particle swarm optimization (PSO) algorithm to solve the path planning problem for multi-vehicle formations in obstacle-dense environments. By integrating a kinematic model of intelligent small robot vehicles (ISRVs) with a refined PSO approach, Li’s work effectively eliminates deadlock phenomena that often plague autonomous navigation, enabling smoother and more efficient coordinated movement. Although their most-cited paper, published in 2018, has garnered 3 citations, it represents a foundational step in addressing complex formation control under constraints. Li’s research is particularly notable for bridging theoretical optimization with practical robotics applications, offering insights that benefit fields like autonomous driving, drone swarms, and industrial logistics. Their work underscores a commitment to advancing intelligent systems that operate reliably in dynamic, obstacle-filled environments—a critical area for future autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1