Papers
6
Total Citations
538
H-Index
5
About
Dr. Yuewei Dai is a leading researcher in autonomous robotics and intelligent navigation systems, with a primary focus on mobile robot path planning, multi-robot coordination, and deep learning applications. Dr. Dai’s most impactful contribution is the development of a reinforcement learning-based path planning method integrated with an improved Dynamic Window Approach, enabling robots to navigate unknown environments with enhanced safety and efficiency—a work that has garnered 284 citations. Expanding on this, Dr. Dai pioneered a hierarchical framework for multi-robot navigation and formation in unknown settings, combining deep reinforcement learning with distributed optimization to improve fault tolerance and task capacity in complex scenarios. Additional notable achievements include advancing facial expression recognition through deep learning (172 citations) and refining the A* algorithm to reduce collision risks and turning redundancies in mobile robot path planning. Dr. Dai’s recent work on LiDAR-based obstacle detection and reasoning-driven artificial potential fields further demonstrates a sustained commitment to robust, real-world navigation solutions. With over 500 total citations, Dr. Dai’s research is essential reading for students and engineers seeking to understand cutting-edge approaches to autonomous navigation and multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Facial expression recognition based on deep learning172 citations · 2022
- 3
- 4The Path Planning of Mobile Robots Based on an Improved A* Algorithm24 citations · 2019
- 5
- 6LiDAR-Based Small-Sized Obstacle Detection for Mobile Robot2 citations · 2024