Keenan Albee

Robotics Technologist,
Jet Propulsion Laboratory
Assistant Professor,
University of Southern California (incoming)

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Picture of Keenan.

I develop algorithms to help autonomous robots operate in extreme environments like the Moon, microgravity, and underwater.

I’m currently at NASA’s Jet Propulsion Lab and will be joining USC in fall 2025.

I’m broadly interested in autonomy for mobile robotic systems operating when conditions are uncertain, unknown, or unstructured. My work integrates tools from optimal control, reinforcement learning, and motion planning, and, increasingly, their interplay with perception for these scenarios. This theme blends real-world assumptions and constraints with environment-aware algorithm design to let robots work where they currently can’t.

Prospective students: Please see here.

Research
About
CV
LASER

Selected publications are available here. You can also find my latest work on Google Scholar.

2024

Image for Lunar Leader: Persistent, Optimal Leader Election for Multi-Agent Exploration Teams

Lunar Leader: Persistent, Optimal Leader Election for Multi-Agent Exploration Teams

Keenan Albee, et al.
MASSPACE @ AAMAS, 2024
link 

Image for AstrobeeCD: Change detection in microgravity with free-flying robots

AstrobeeCD: Change detection in microgravity with free-flying robots

Holly Dinkel, Julia Di, Jamie Santos, Keenan Albee, et al.
Acta Astronautica, 2024
link  doi 

Image for Multi-Agent Autonomy for Space Exploration on the CADRE Lunar Technology Demonstration Mission

Multi-Agent Autonomy for Space Exploration on the CADRE Lunar Technology Demonstration Mission

J.P. de la Croix, Federico Rossi, Roland Brockers, Dustin Aguilar, Keenan Albee, et al.
IEEE Aerospace, 2024
link  doi 

Image for The ReSWARM Microgravity Flight Experiments: Planning, Control, and Model Estimation for On-Orbit Close Proximity Operations

The ReSWARM Microgravity Flight Experiments: Planning, Control, and Model Estimation for On-Orbit Close Proximity Operations

Bryce Doerr and Keenan Albee and Monica Ekal, et al.
Journal of Field Robotics, 2024
link  doi  code 

2022

Image for Autonomous Rendezvous with an Uncertain, Uncooperative Tumbling Target: The TumbleDock Flight Experiments

Autonomous Rendezvous with an Uncertain, Uncooperative Tumbling Target: The TumbleDock Flight Experiments

Keenan Albee, et al.
ESA ASTRA, 2022
link  code 

Image for The RATTLE Motion Planning Algorithm for Robust Online Parametric Model Improvement with On-Orbit Validation

The RATTLE Motion Planning Algorithm for Robust Online Parametric Model Improvement with On-Orbit Validation

Keenan Albee and Monica Ekal, et al.
Robotics and Automation, Letters, 2022
link  doi  code 

2021

Image for On-Orbit Inspection of an Unknown, Tumbling Target using NASA’s Astrobee Robotic Free-Flyers

On-Orbit Inspection of an Unknown, Tumbling Target using NASA’s Astrobee Robotic Free-Flyers

Charles Oestreich, Antonio Teran, Jessica Todd, Keenan Albee, Richard Linares
CVPR, 2021
link  doi 

Image for A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets

A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets

Keenan Albee and Charles Oestreich, et al.
Frontiers in Robotics and AI, 2021
link  doi 

Image for Online Information-Aware Motion Planning with Inertial Parameter Learning for Robotic Free-Flyers

Online Information-Aware Motion Planning with Inertial Parameter Learning for Robotic Free-Flyers

Monica Ekal and Keenan Albee, et al.
IROS, 2021
link  doi 

Projects and Platforms

I like to get robots into the field to uncover new algorithmic insights and verify performance in complex situations that often break initial algorithmic assumptions. My algorithms have flown on-orbit multiple times and I am responsible for multiple autonomy “firsts” that will fly to the moon on NASA’s CADRE lunar rovers in the near future on the Intuitive Machines-3 lander1. My work includes the first autonomous on-orbit rendezvous with an uncharacterized tumbling target; the (soon-to-be!) first model predictive controller to run on another celestial body; and the (soon-to-be!) first distributed algorithm in a multi-agent space exploration mission. I was a contributing developer to NASA’s Astrobee platform2, and was the last researcher to work with MIT’s SPHERES platform. My favorite applications are in the space domain, including planetary surface robotics, microgravity robotics, and other canonical problem areas like powered descent guidance. I also work on broadly applicable platforms, including medical robotic devices, maritime robotics, and ground vehicle robotics.

Education

  • Ph.D. in Aeronautics and Astronautics (Autonomous Systems), Massachusetts Institute of Technology, 2022
  • S.M. in Aeronautics and Astronautics, Massachusetts Institute of Technology, 2019
  • B.S. in Mechanical Engineering, Columbia University, 2017

I received a Ph.D. in aeronautics and astronautics (autonomous systems) from MIT in 2022 under a NASA Space Technology Research Fellowship. Before that, I received my B.S. in mechanical engineering (minors in computer science and history) at Columbia Univeristy in 2017. You can find my full CV here.

Research Interests

Robotic motion planning; safe motion planning under uncertainty; model predictive control, optimal control, and trajectory optimization; reinforcement learning; information-theoretic planning; space systems.

Everything Else

I’m an avid backpacker, skier, and gravel biker/bikepacker. I also scuba dive and am a private pilot, and am always working on finding more time for all of the above alongside research. Interestingly enough, many of my hobbies revolve around making real-time planning decisions for dynamical systems in uncertain environments, so they might be considered field work :).

  1. Acknowledgment to my many collaborators here including but not limited to: Abhishek Cauligi, Brian Coltin, Monica Ekal, Federico Rossi, Sriramya Bhamidipati, Caroline Specht, Roberto Lampariello, and others. ↩

  2. Here is my flight software guide for autonomy researchers using Astrobee, a fantastic research platform developed by NASA Ames’ Intelligent Robotics Group. ↩

I will be joining the faculty at the University of Southern California in Fall 2025! The Laboratory for Autonomous Systems in Exploration and Robotics (LASER) will continue to pursue exciting research in extreme environment robotic autonomy.

Motivated students with backgrounds in robotics, aerospace/mechanical engineering, computer science, controls, and related fields are encouraged to apply for Ph.D. or research-based S.M. positions. Please indicate your interest on your application materials to USC Viterbi. You can also email me directly with your CV at kalbee@usc.edu with subject line [LASER-APPLY].