Yanghe Feng
Papers
2
Total Citations
6
H-Index
2
About
Yanghe Feng is a researcher whose work bridges the critical gap between theoretical control systems and practical mobile robotics. His primary research areas include mobile robot local planning, multi-agent systems, and learning-based control. Feng’s most significant contribution is the development of **MRPB 1.0**, a unified benchmark for evaluating mobile robot local planning approaches. This benchmark provides a standardized framework to assess and compare local planning algorithms—a key technology for full robot autonomy—addressing a long-standing need for reproducible and comprehensive evaluation in the field. His work on **heuristic dynamic programming-based learning control** for discrete-time disturbed multi-agent systems further demonstrates his expertise in adaptive control, offering robust solutions for complex, distributed environments. While his citation counts are currently modest (4 and 2 citations respectively), the foundational nature of his benchmark work positions it as a potential standard for future robotics research. Feng’s contributions are particularly valuable for students and researchers seeking rigorous, comparable evaluation tools in mobile robotics and multi-agent control.
Research Focus
Key Achievements
Top Papers
- 1
- 2