Papers
12
Total Citations
85
H-Index
6
About
Keenan Albee is a leading researcher in autonomous space robotics, specializing in multi-agent coordination, on-orbit inspection, and adaptive motion planning for extreme environments. His most impactful work includes the CADRE lunar technology demonstration, which pioneers multi-agent autonomy for a team of three rovers and a base station slated to land at the Moon’s Reiner Gamma region—a mission that has already garnered 20 citations. Albee also developed practical methods for on-orbit inspection of unknown, tumbling targets using NASA’s Astrobee robotic free-flyers aboard the International Space Station, achieving 16 citations. His contributions extend to the ReSWARM microgravity flight experiments, which advance planning, control, and model estimation for on-orbit assembly and repair. With a focus on online information-aware motion planning and inertial parameter learning, Albee has demonstrated how autonomous free-flyers can quantify system uncertainties in safety-critical space operations. His work on the RATTLE algorithm and Dyna reinforcement learning framework further enables robust parametric model improvement and reactive close proximity operations. With over 80 total citations across his top papers, Albee’s research is pivotal for future planetary exploration and autonomous space infrastructure.
Research Focus
Key Achievements
Top Papers
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- 9AstrobeeCD: Change detection in microgravity with free-flying robots4 citations · 2024
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