Papers
1
Total Citations
15
H-Index
1
About
Xinnan Hu is a researcher whose work lies at the intersection of robotics, optimization algorithms, and intelligent navigation systems. Their most cited contribution, "Robot Path Planning Based on Random Coding Particle Swarm Optimization" (2015), addresses a fundamental challenge in mobile robotics: finding optimal, collision-free paths in obstacle-dense environments. By introducing a random coding mechanism into particle swarm optimization, Hu’s approach enhances the algorithm’s ability to escape local optima and converge on efficient routes—a critical advancement for autonomous navigation. With 15 citations, this work has influenced subsequent studies in swarm intelligence and path planning, demonstrating Hu’s impact on practical robotics. The research elegantly tackles the dual constraints of path feasibility and obstacle avoidance, offering a robust solution that balances computational efficiency with real-world applicability. Hu’s contributions are particularly valuable for students and engineers seeking to understand how metaheuristic optimization can be tailored for mobile robot control, bridging theoretical algorithm design with tangible robotic movement.
Research Focus
Key Achievements
Top Papers
- 1Robot Path Planning Based on Random Coding Particle Swarm Optimization15 citations · 2015