145 citations · 811 across the 39 of their papers we have counts for
6 papers · 1 filter
The ReSWARM Microgravity Flight Experiments: Planning, Control, and Model Estimation for On-Orbit Close Proximity Operations
Bryce Doerr, Keenan Albee, Monica Ekal +2
On-orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on-orbit ass…
The RATTLE Motion Planning Algorithm for Robust Online Parametric Model Improvement with On-Orbit Validation
Keenan Albee, Monica Ekal, Brian Coltin +3
Certain forms of uncertainty that robotic systems encounter can be explicitly learned within the context of a known model, like parametric model uncertainties such as mass and mome…
Online Information-Aware Motion Planning with Inertial Parameter Learning for Robotic Free-Flyers
Monica Ekal, Keenan Albee, Brian Coltin +3
Space free-flyers like the Astrobee robots currently operating aboard the International Space Station must operate with inherent system uncertainties. Parametric uncertainties like…
Safe and Uncertainty-Aware Robotic Motion Planning Techniques for Agile On-Orbit Assembly
Bryce Doerr, Keenan Albee, Monica Ekal +2
As access to space and robotic autonomy capabilities move forward, there is simultaneously a growing interest in deploying large, complex space structures to provide new on-orbit c…
Motion Planning and Control for On-Orbit Assembly using LQR-RRT* and Nonlinear MPC
Bryce Doerr, Richard Linares
Deploying large, complex space structures is of great interest to the modern scientific world as it can provide new capabilities in obtaining scientific, communicative, and observa…
Combining Parameter Identification and Trajectory Optimization: Real-time Planning for Information Gain
Keenan Albee, Monica Ekal, Rodrigo Ventura +1
Robotic systems often operate with uncertainties in their dynamics, for example, unknown inertial properties. Broadly, there are two approaches for controlling uncertain systems: d…