Yuxue Cao
Papers
1
Total Citations
2
H-Index
1
About
Yuxue Cao is a robotics researcher whose work focuses on intelligent control systems for next-generation exploratory robots operating in extreme environments. Their primary research areas include reinforcement learning-based motion control, multi-motion mode robotics, and autonomous navigation for space exploration. Cao’s most notable contribution is the development of a velocity control system for a multi-motion mode spherical probe robot, which addresses critical limitations of traditional wheeled and tracked robots in harsh, unknown terrains. By applying reinforcement learning algorithms, Cao enables these spherical robots to adapt their locomotion strategies dynamically, enhancing mobility and operational density in deep space missions. This work, published in 2023, has already garnered attention with 2 citations, signaling growing interest in adaptive control for space robotics. Cao’s research bridges the gap between machine learning and practical robotic design, offering a scalable solution for autonomous exploration on other planets or hazardous environments on Earth. Their innovative approach to combining reinforcement learning with multi-modal locomotion positions them as an emerging contributor to the field of space robotics and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1