Yuxin Wei
Papers
1
Total Citations
2
H-Index
1
About
Yuxin Wei is a researcher at the forefront of intelligent robotics, with a primary focus on developing advanced control systems for autonomous navigation. Their most cited work, "Robot Obstacle Avoidance Controller Based on Deep Reinforcement Learning" (2022), addresses a critical challenge in mobile robotics: enabling safe, efficient movement through unpredictable environments. While traditional obstacle avoidance methods rely on static path planning or guidance—often failing in complex, dynamic settings—Wei’s contribution leverages deep reinforcement learning to create a controller that adapts in real time, substantially improving robot stability and operational efficiency. This work, with 2 citations, lays a foundational framework for integrating learning-based decision-making into robotic systems. Wei’s research sits at the intersection of reinforcement learning, control theory, and mobile robotics, aiming to bridge the gap between simulation and real-world deployment. Their approach not only enhances robot autonomy but also offers scalable solutions for applications in logistics, service robotics, and autonomous vehicles. As the field moves toward more adaptive and resilient machines, Yuxin Wei’s contributions represent a meaningful step forward in making robots truly capable of navigating the unpredictable human world.
Research Focus
Key Achievements
Top Papers
- 1Robot Obstacle Avoidance Controller Based on Deep Reinforcement Learning2 citations · 2022