Xiaoqian Qi
Papers
2
Total Citations
24
H-Index
2
About
Xiaoqian Qi is a researcher focused on advancing autonomous multi-robot systems and intelligent path planning. Their work primarily addresses the challenges of navigation and target searching in complex, obstacle-rich environments. A key contribution is the development of a novel path planning method that integrates the Gray Wolf Optimization algorithm with self-powered sensor technology, enabling mobile robots to navigate efficiently and autonomously. This work, published in 2023, has already garnered 20 citations, highlighting its immediate relevance to the field. Qi has also made notable strides in cooperative robotics by proposing a hybrid algorithm that combines Particle Swarm Optimization and Bacterial Foraging Optimization. This approach overcomes the limitations of local minima and slow convergence in multi-robot target searching tasks, demonstrating a sophisticated understanding of bio-inspired computation. Through these contributions, Qi is helping to shape the future of intelligent, autonomous robotic systems, with a clear impact on both theoretical optimization and practical robotic applications.
Research Focus
Key Achievements
Top Papers
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- 2