Session
Poster Session 4
Location
Salt Palace Convention Center, Salt Lake City, UT
Abstract
ROC-ML is a European Space Agency (ESA) funded project led by Craft Prospect in collaboration with University of Glasgow. The project leverages Machine Learning (ML) approaches to augment the performance of robust motion planning in space applications. The developed method of spacecraft motion planning must be suitably computationally efficient to be deployed on low SWAP space hardware.
Document Type
Event
Included in
Robust Learning-Based Guidance for Close Proximity Operation Scenarios
Salt Palace Convention Center, Salt Lake City, UT
ROC-ML is a European Space Agency (ESA) funded project led by Craft Prospect in collaboration with University of Glasgow. The project leverages Machine Learning (ML) approaches to augment the performance of robust motion planning in space applications. The developed method of spacecraft motion planning must be suitably computationally efficient to be deployed on low SWAP space hardware.
