Linfei Yin

About

Linfei Yin is a pioneering researcher at the intersection of power systems, artificial intelligence, and robotics. His work centers on developing intelligent dispatch mechanisms for next-generation energy grids and autonomous path planning for mobile robots. Yin’s most influential contribution is his comprehensive review on machine learning for smart dispatch in power systems (2019), which has garnered 77 citations, establishing a foundational framework for integrating AI into grid operations. He has also advanced the field of cyber-physical-social systems, proposing a Smart Energy Robotic Dispatcher that automates knowledge-driven energy management (2018, 22 citations). In robotics, Yin introduced a novel Fuzzy A* quantum multi-stage Q-learning artificial potential field algorithm (2024, 22 citations), demonstrating a sophisticated fusion of quantum computing and reinforcement learning for mobile robot navigation. His latest work on the MAPPO-ITD3-IMLFQ algorithm (2025) further pushes boundaries in multi-robot path planning. Yin’s research uniquely bridges theoretical AI advances with practical energy and robotics applications, making him a key figure in the evolution of autonomous, intelligent systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A review of machine learning for new generation smart dispatch in power systems

   77 citations · 2019
2. 2
   Fuzzy A∗ quantum multi-stage Q-learning artificial potential field for path planning of mobile robots

   22 citations · 2024
3. 3
   Cyber-physical-social Systems Based Smart Energy Robotic Dispatcher and Its Knowledge Automation: Framework, Techniques and Challenges

   22 citations · 2018
4. 4
   MAPPO-ITD3-IMLFQ algorithm for multi-mobile robot path planning

   3 citations · 2025

Key Collaborators

Contact & Links