This multidisciplinary program of basic and applied research addresses the challenges of autonomous on-orbit space operations. A novel program of mathematical, computational and engineering research addresses foundational challenges in 1) digital twin technology, 2) feedback control algorithms and 3) human-machine-aware supervisory schemes, all in the context of space systems. A campaign of experimental validation and demonstration in multiple testbeds serves to integrate the research advances; validate, robustify and harden the algorithms; and enable transition of research products into DoD applications. Key novel research ideas include: 1) a probabilistic graphical model foundation for digital twins that automates model calibration and updating, makes data-model integration scalable across many assets and quantifies uncertainty; 2) new feedback control algorithms that leverage model predictive control to achieve control for on-orbit space operations under stringent constraints, and handle uncertainty by accounting for hybrid and set-valued dynamics; 3) new human-machine-aware supervisory schemes targeting uncertain and contested operating environments, synthesized as hybrid control schemes that coordinate control algorithms across different phases of the mission, address recovery from unexpected conditions, and incorporate the role of potential human intervention. Experimental demonstration in testbeds covers mission-specific features in three case studies: on-orbit assembly, decommissioning and towing, and on-orbit refueling. Experiments will be conducted at ERAU, UCSC, NPS, and AFRL/RV, specifically, in the multiple testbeds at the ROC lab, the BONSAI lab, the SPACER lab, and the LINCS lab. The experimental phase is a stepping stone for the development of a flight demonstration in collaboration with AFRL/RV and industry partners. The effort involves industry partners with unique expertise in space operations and the case studies driving the project.