Comprehensive Assessment of Orbital Robotics, Space Application Simulation/Machine Learning, and Methods of Hardware in the Loop Validation

Abstract

The space industry's continued focus and advances in safe reusable launch vehicles have ushered in a new affordable age of space flight, enabling a wider range of enterprises and organizations to launch and operate space-based assets in low earth orbit and beyond. Ensuring and extending mission life cycles of these orbital assets to include launch vehicles, satellites, and space stations will require a new generation of adaptive, robust, and autonomous robotic systems. Merging proven orbital dynamics, relative motion, robotic kinematics, and spacecraft rendezvous/docking with new advances in Machine Learning, Computer Vision, Data communications, and many more exciting fields of study. These efforts intend to provide future enterprises with the capability to perform On-Orbit Servicing and Maintenance (OSAM) of failed or damaged space assets, in-space assembly of new platforms, and manufacturing of com-ponents. However, the means to validate individual hardware and software components of these technologies and test the collaborative “system of systems” at a large scale are still largely in their development stages. This paper is a comprehensive survey and assessment of the current and near-future technical developments in the fields of space simulation and validation, orbital robotics, and space-based automation; identifying the current gaps and capability necessary for large scale industry validation and employment of these systems. Finally, it will also illustrate some of the on-going research being conducted at Virginia Tech's space labs to address some of these gaps in the future.