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David W. Miller

2 accepted papers

2022

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

RA-L 2022

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 moments of inertia. Quantifying such parametric uncertainty is important for more accurate prediction of the system behavior

Cited by 5SourceScholar
2021

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

IROS 2021poster

Space free-flyers like the Astrobee robots currently operating aboard the International Space Station must operate with inherent system uncertainties. Parametric uncertainties like mass and moment of inertia are especially important to quantify in these safety-critical space systems and can change i…

Cited by 11SourceScholar