Vacuum Impregnation Process for Extraterrestrial Realization (VIPER) is an ISS payload designed to advance the Vacuum Pressure Impregnation (VPI) process on a space station payload. The VPI process increases the dielectric strength of an electrical assembly, enhances thermal insulation properties, and mitigates catastrophic issues caused by Foreign Object Debris (FOD) that can get caught in the system, such as Lunar regolith. Expansion of power systems on orbit benefits colonization efforts in space, maturing motor generator manufacturing processes that impact fluid management systems and habitat safety. Development and processing of electrical windings using the VPI process diminishes launch risks and reduces the need for resupply missions for deep space applications. VIPER fosters increased self-reliance of space-based processes through enhanced VPI procedures for better power generation development in space.
The Decluttering Earth Orbit to Repurpose for Bespoke Innovative Technologies (DEORBIT) signifies a shift in development within Martian Sky, as greater focus is being placed in Rendezvous and Proximity Operations (RPO) capabilities. The technology provided the basis for ROGUES and COVERT technologies within the Martian Sky ecosystem, assessing methods to leverage computer vision to gain actionable information from an observed satellite. Initial studies from DEORBIT investigated methods clear debris objects from an orbit ahead of supporting downstream manufacturing and assembly technologies utilizing a single satellite architecture.
Robust Object Grasping Utilizing Estimated States (ROGUES) incorporates advanced computer vision techniques into a satellite designed to interact with and maneuver debris objects or satellites, termed as clients. The goal of ROGUES is to build a mission development tool and subsequent satellite hardware that enables client interactions in space.
Client-Oriented Vision-Enhancing Recognition Technology (COVERT) combines advanced computer vision techniques with Artificial Intelligence/Machine Learning (AI/ML) capabilities to improve satellite-to-satellite interactions in close proximity. AI/ML in COVERT, known as the Martian Sky Satellite Component Interpretation Network (SCINet) allows for satellite subsystem identification on a client that leads to improvements for industries such as satellite servicing.