Youtai Xue
Papers
1
Total Citations
5
H-Index
1
About
Youtai Xue is a researcher in robotics and autonomous systems, with a focus on intelligent navigation and collision avoidance in dynamic environments. His most cited work, "Autonomous robot navigation with self-learning for collision avoidance with randomly moving obstacles" (2014), introduces a hierarchical control framework that combines high-level Q-learning for strategic path planning with low-level appearance-based visual servoing for real-time obstacle evasion. This approach enables robots to adaptively and safely navigate through unpredictable settings, a critical challenge in autonomous mobile robotics. With 5 citations, this paper demonstrates a foundational contribution to self-learning navigation systems. Xue’s research bridges reinforcement learning and computer vision, offering practical solutions for robots operating in cluttered, human-populated spaces. His work is particularly relevant for applications in service robotics, autonomous vehicles, and industrial automation, where safe interaction with moving obstacles is essential. By integrating learning-based decision-making with robust visual feedback, Xue advances the development of truly autonomous agents capable of operating in the real world.
Research Focus
Key Achievements
Top Papers
- 1