Yunfei Cui
Papers
1
Total Citations
7
H-Index
1
About
Yunfei Cui is a rising researcher in the field of intelligent robotics and autonomous navigation, with a primary focus on multi-objective path planning and deep reinforcement learning. Their most notable contribution, the 2022 paper "Multi-objective path planning based on deep reinforcement learning," introduces a hierarchical Twin Delayed Deep Deterministic policy gradient approach to solve the complex challenge of planning safe, shortest paths for robots tasked with visiting multiple target areas. This work, which has garnered 7 citations, addresses a critical gap in enabling robots to efficiently sequence and execute diverse tasks in dynamic environments. By integrating deep reinforcement learning with multi-objective optimization, Cui's research offers a robust framework for balancing safety and efficiency—a key requirement for real-world robotic applications. Their work stands out for its practical relevance, providing a foundation for future advancements in autonomous systems, from warehouse logistics to search-and-rescue missions. As an emerging voice in their field, Cui's contributions are paving the way for more intelligent, adaptive robotic decision-making.
Research Focus
Key Achievements
Top Papers
- 1Multi-objective path planning based on deep reinforcement learning7 citations · 2022