Pengqian Han
Papers
1
Total Citations
36
H-Index
1
About
Pengqian Han is a researcher whose work lies at the intersection of swarm intelligence algorithms, autonomous navigation, and industrial robotics. Han's most significant contribution is the development of a novel path planning method for intelligent patrol cars—specialized robots used for equipment defect detection in environments like power distribution rooms and data centers. Specifically, Han introduced a Multi-Objective Cauchy Mutation Cat Swarm Optimization Algorithm, which enhances the efficiency and robustness of autonomous navigation systems by improving the cat swarm optimization technique with Cauchy mutation to better handle multi-objective path planning challenges. This work, published in 2020, has garnered 36 citations, reflecting its relevance in the growing field of industrial automation and mobile robotics. Han's research addresses critical needs in smart infrastructure maintenance, offering practical solutions for autonomous inspection systems. By advancing optimization algorithms for real-world navigation tasks, Han has contributed to the broader application of swarm intelligence in robotics, making industrial environments safer and more efficient through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1