Shaoyu Yang

Institute of Science Tokyo

Papers

1

Total Citations

2

H-Index

1

About

Shaoyu Yang is a rising researcher in robotics and autonomous systems, with a primary focus on kinodynamic motion planning—the challenge of generating safe, efficient, and dynamically feasible trajectories for vehicles. His most impactful work introduces a stochastic template-based RRT* algorithm that achieves asymptotic optimality while dramatically improving computational efficiency over traditional methods. By cleverly precomputing motion primitives and incorporating stochastic sampling, Yang’s approach reduces the planning time without sacrificing trajectory quality, addressing a critical bottleneck in real-time autonomous driving. Though early in his career, his 2025 paper has already garnered attention, and his contributions are poised to influence next-generation motion planners for self-driving cars and mobile robots. Yang’s research bridges the gap between theoretical guarantees and practical deployment, making him a promising voice in the field of robotics and intelligent transportation systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Efficient and Asymptotically Optimal Vehicle Motion Planning With Stochastic Template-Based RRT*
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Institute of Science Tokyo

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago