Papers

1

Total Citations

215

H-Index

1

About

Shuai Long is a leading researcher in mobile robotics and intelligent path planning, with a particular focus on bio-inspired optimization algorithms. His most influential work, "Mobile Robot Path Planning Based on Ant Colony Algorithm With A* Heuristic Method" (2019), has garnered over 215 citations, demonstrating its significant impact on the field. In this seminal paper, Long introduces a novel hybrid approach that synergistically combines the A* algorithm’s heuristic efficiency with the MAX-MIN Ant System’s adaptive exploration capabilities. By constructing a grid-based environmental model, his method dramatically improves the convergence speed and search quality of traditional ant colony algorithms, enabling mobile robots to navigate complex, obstacle-rich maps with unprecedented reliability. This contribution addresses a critical bottleneck in autonomous navigation, offering a practical solution for real-world applications from warehouse logistics to search-and-rescue operations. Long’s work stands out for its elegant integration of deterministic and stochastic optimization strategies, providing a robust framework that has inspired subsequent advances in swarm intelligence and robotic motion planning. His research continues to shape how autonomous systems perceive and traverse challenging environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
215
Total Citations
215
Avg Citations/Paper
🏆 Most Cited Paper
Mobile Robot Path Planning Based on Ant Colony Algorithm With A* Heuristic Method
215 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Electronic Science and Technology of China

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago