Papers

3

Total Citations

160

H-Index

3

About

Biwei Tang is a leading researcher in mobile robotics and swarm intelligence, with a focus on solving complex path planning and multi-robot coordination problems. His major contributions center on enhancing particle swarm optimization (PSO) algorithms to address NP-hard challenges in global path planning for mobile robots. Tang's seminal 2016 paper, "Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning," has garnered 80 citations, establishing a hybrid approach that improves convergence and solution quality. He further advanced the field with a convergence-guaranteed PSO method (2017, 42 citations), introducing a random-disturbance self-adaptive mechanism to ensure robust path generation in complex environments. Tang also tackled multi-robot task allocation with an improved PSO approach (2017, 38 citations), demonstrating the scalability of his techniques for cooperative robotics. His work is notable for its practical impact on autonomous navigation and multi-agent systems, offering efficient, high-quality solutions that bridge theoretical optimization and real-world robotic applications. Tang's research continues to inspire innovations in adaptive swarm intelligence and autonomous systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
160
Total Citations
53
Avg Citations/Paper
🏆 Most Cited Paper
Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning
80 citations · 2016
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Northwestern Polytechnical University, Systems Dynamics (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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