Changzhi Yan
Papers
1
Total Citations
23
H-Index
1
About
Changzhi Yan is a leading researcher in the field of intelligent robotics and autonomous space systems, with a particular focus on control strategies for free-floating space robots. His most-cited work, "Control of Free-Floating Space Robots to Capture Targets Using Soft Q-Learning" (2018, 23 citations), introduces a groundbreaking approach that leverages soft Q-learning (SQL) to enable space robots to capture moving targets without requiring prior knowledge of the system’s dynamic models. This innovation addresses a critical challenge in space debris removal and on-orbit servicing, offering a model-free, adaptive solution that trains stochastic energy-based policies for robust target capture. Yan’s contributions stand out for their practical significance in unstructured environments, where traditional control methods often fail. By integrating reinforcement learning with space robotics, his work has opened new avenues for autonomous operations in zero-gravity conditions. With 23 citations, this paper has already influenced subsequent research in intelligent control and space automation, marking Yan as a rising talent in the intersection of machine learning and aerospace engineering.
Research Focus
Key Achievements
Top Papers
- 1