Papers
3
Total Citations
29
H-Index
2
About
Caizhi Fan is a robotics researcher whose work bridges the frontiers of space robotics and multi-agent systems. His primary contributions lie in the control of free-floating space robots, where he has developed innovative methods for manipulating passive objects during on-orbit servicing. His most cited paper, "Task space control of free-floating space robots using constrained adaptive RBF-NTSM" (2014, 21 citations), introduces a robust finite-time control approach that ensures high-precision manipulation without disturbing the robot's base attitude—a critical challenge for space missions. This work, along with his study on "Reactionless robust finite-time control for manipulation of passive objects" (2014, 6 citations), demonstrates his ability to solve complex, real-world problems in microgravity environments. More recently, Fan has explored multi-agent reinforcement learning for swarm robotics, as seen in his 2019 paper on "Biased Experience Sharing" (2 citations), which addresses collaborative learning in non-deterministic settings. His research not only advances autonomous space operations but also contributes to the broader field of robot learning, making him a notable figure in both space and swarm robotics.
Research Focus
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Top Papers
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