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IN-PASS: Intelligent Navigation, Planning, and Autonomy for Swarm Systems
Phone: (240) 391-3310
Email: ken.center@orbitlogic.com
Phone: (240) 391-3310
Email: ken.center@orbitlogic.com
Address:
Type: Nonprofit College or University
Orbit Logic is teamed with the University of Colorado Boulder to develop the Intelligent Navigation, Planning, and Autonomy for Swarm Systems (IN-PASS) Solution, which builds on Orbit Logicrsquo;s proven Autonomous Planning System (APS) decentralized planning framework to enable the configuration and execution of collaborative mission concepts. Assessments can be performed completely virtually within an open simulation environment, or can be deployed to physical assets in a testbed or operational environment.We apply IN-PASS to heterogeneous swarms of Lunar orbital and surface assets.nbsp; For example, the satellite constellation overhead plans sensor collections in support of multiple objectives ndash; surface asset localization and surface chemistry detection. APS plans the delivery of data products to a surface asset with high computing capacity, where algorithms are invoked and output the location of rovers and areas of interest (AOIs) for contact science. Location measurements allow Decentralized Data Fusion to maintain shared team awareness - critical to the teamrsquo;s ability to autonomously coordinate. AOI events are trigger events for rovers to navigate to the location. A formal methods approach to onboard planning is employed on the rover assets that utilizes a Markov Data Process to balance performance, resource usage and safety. This is particularly important for inter-asset communications or localization - operational functions that utilize significant stored energy.Astronauts can participate in-the-loop with these swarms using devices running interactive user interfaces that allow them to a) specify mission goals, b) receive feedback on the satisfaction of their requests as the team performs the associated tasks, c) receive and display the end data associated with their requests, and d) actually collaborate with the autonomous robots by electing to assume tasks they are well suited to perform.
* Information listed above is at the time of submission. *