Motion and Pose Estimation for Autonomy of Dynamic/Contact Tasks

Machine vision technology is a maturing field. This project seeks to move the technology from the theoretical and controlled-environment testing to a prototype stage for use in a space environment with a cluttered field and dynamic effects. In the end, the prototype system will demonstrate operational feasibility of using machine vision to provide supervised automation for target alignment/grasping strategies. This project seeks to advance motion and pose estimation in support of dexterous robotics operations. Existing edge detection and model-based feature tracking methods will be used as the starting point for evolving a more robust technique for use in a dynamic environment. The challenges to overcome are related to dynamic effects of manipulator motion and orbital lighting.

Efficiencies for ISS robotics operations which translates to time savings which can be used for science. Enabling machine vision and natural feature tracking technology for Evolvable Mars Campaign mission capabilities for both ground tele-robotics and crew-assisted robotics operations in dynamic tasks like grapple, grasp, and payload/ORU install operations.

This is early/mid-stage (TRL 6) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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