Haoyi Li
Papers
1
Total Citations
1
H-Index
1
About
Haoyi Li is a researcher at the forefront of autonomous robotics and artificial intelligence, with a focused expertise in reinforcement learning for mobile robot navigation. His most-cited work, "Research on Path Planning of Autonomous Mobile Robot Based on Reinforcement Learning" (2024), introduces a groundbreaking integration of Deep Q-Networks (DQN) with Prioritized Experience Replay (PER) to significantly enhance path-planning efficiency. By modeling DQN behavior through the lens of quantum dot simulations, Li’s approach achieves superior learning performance, enabling robots to navigate complex environments with unprecedented adaptability. This contribution addresses a critical bottleneck in autonomous systems—balancing exploration and exploitation in real-time decision-making. With 1 citation already in its first year, the paper signals growing recognition of Li’s innovative methodology. His work bridges theoretical reinforcement learning advances with practical robotics applications, offering a scalable framework for intelligent navigation. Li’s research holds promise for transforming industries reliant on autonomous mobility, from logistics to search-and-rescue, marking him as a rising voice in the intersection of AI and robotics.
Research Focus
Key Achievements
Top Papers
- 1