Yiduo Yao
Papers
1
Total Citations
28
H-Index
1
About
Yiduo Yao is a leading researcher at the forefront of artificial intelligence and robotics, with a primary focus on deep reinforcement learning (DRL) for autonomous navigation in complex, dynamic environments. His most-cited work, the 2025 review "Deep Reinforcement Learning of Mobile Robot Navigation in Dynamic Environment," has already garnered 28 citations, establishing a critical foundation for the field. Yao’s major contribution lies in identifying and addressing a key gap in existing research: while most studies concentrate on simplified dynamic scenarios or static environment modeling, his work systematically analyzes the challenges of real-world, unpredictable settings. By synthesizing state-of-the-art DRL approaches, he provides a roadmap for developing more robust, adaptive navigation systems that can handle moving obstacles and changing conditions. This review has become an essential reference for researchers seeking to advance beyond idealized simulations toward practical deployment. Yao’s insights are shaping the next generation of intelligent mobile robots, from warehouse logistics to autonomous vehicles, making his work highly influential for both students and practitioners aiming to bridge the gap between theoretical DRL and real-world robotic autonomy.
Research Focus
Key Achievements
Top Papers
- 1