Deploying SVGS on small, powerful, inexpensive platforms opens the path to use SVGS as rendezvous & docking sensor in multiple space applications. Key factors that make SVGS attractive to small sat applications (small form factor, low-power consumption, relatively simple implementation) also make it appealing to human exploration missions, where crew vehicles need to dock with a variety of platforms. The niche for a proximity operations sensor for space applications is currently open – this initiative is positioning SVGS to compete for that role. SVGS is envisioned as a compact, low-cost, sensing and estimation system for proximity operations and rendezvous applications in space robotics. The proposed effort will help demonstrate SVGS performance while being very competitive in size, complexity and cost compared to currently existing devices. 1) SVGS can support orientation and navigation in cubesat and smallsat missions. Automatic docking and maneuvering cubesats can be used for inspection tasks related to manned spacecraft. 2) Cubesats capable of vision-based positioning and orientation can also be used to perform close-up science missions. 3) Additional potential applications include orbital debris mitigation, & small sat formation flying. 4) SVGS could be used as sensor that assists large spacecraft docking or feedback for robotic systems, similar to the role played by the camera and RMS target when astronauts maneuvered the Remote Manipulator System on the Space Shuttle.
The proposed effort will deliver a positioning/metrology system well suited for proximity operations in Robotics when vision-based feedback is desirable, such as in automated docking or approach/grasp tasks with a robotic hand. It would also be well suited for rendezvous, short range navigation and visual inspection tasks in Cubesats. The SVGS/RINGS architecture can support a broad array of space missions - potential customers are contractors or companies supporting missions with small robots that need to dock, proximity maneuvers or teleoperation. SVGS will evolve as an “agnostic" architecture that can be ported to any platform. To make SVGS available to many possible users, a 'portable' version of SVGS will be developed and maintained: a version of the SVGS algorithm that is agnostic to platform or language. SVGS can be implemented in ANSI C and provide an API with bindings for Python, Java, etc., to broaden its applicability. The API would be purely the image processing and mathematical portions of the SVGS algorithm, leading to the development of a 'root' version of SVGS that any potential customer could easily adapt and use in a variety of platforms and applications.
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