Shulin Wang

Shanghai Jiao Tong University

Papers

1

Total Citations

16

H-Index

1

About

Shulin Wang is a researcher whose work lies at the intersection of intelligent robotics and deep-sea resource extraction, with a particular focus on autonomous navigation and path planning for underwater vehicles. Wang’s most impactful contribution to date is the development of an improved particle swarm optimization (PSO) algorithm for three-dimensional path planning of deep-sea mining vehicles (DSMVs). This work, published in 2023 and already garnering 16 citations, directly addresses a critical bottleneck in underwater robotics: the tendency of conventional PSO algorithms to become trapped in local optima and converge slowly in complex, three-dimensional underwater environments. By enhancing the algorithm’s ability to make robust path decisions and avoid obstacles, Wang’s research provides a practical framework for safer and more efficient autonomous operations in extreme deep-sea conditions. This contribution is particularly significant given the growing global interest in seabed mining and the need for reliable, intelligent vehicles to operate in these hazardous, remote environments. Wang’s work is a valuable resource for researchers and engineers developing autonomous systems for marine exploration and resource extraction.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization
16 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago