Orbit Logic's existing Autonomous Planning System (APS) is the foundation of the IN-PASS architecture. An instance of APS will operate onboard each swarm asset to provide asset level resource planning and independence as well as to enable autonomous cooperation between assets over intermittently available communication links.
Under this effort, Orbit Logic will develop the human-robot teaming in APS so that astronauts or mission operators can interact as "humans-on-the-loop" with IN-PASS to provide guidance, shape mission objectives, and directly participate by handling tasks that are uniquely suited to human dexterity or cognition. The net result will be that humans will be able to leverage the full capabilities of a heterogeneous robotic swarm without micromanaging the actions of each individual asset.
CU's Event-Triggered Decentralized Data Fusion (ET-DDF) algorithm will maintain a common relevant operations picture (CROP) with minimal data exchange. Specialized communication models will be developed to simulate this data exchange accurately. Finally, Linear Temporal Logic (LTL) will be used for task specification and multi-objective control policies will be designed to tradeoff navigation performance and resource use onboard rovers. In addition, CU's ASPEN lab will provide an environment for mixed-mode hardware testing with real wheeled robots.
APS is a powerful technology that can be leveraged for autonomous planning in any domain. The breadth of its applications proves its flexibility; beyond robotic Lunar exploration, Orbit Logic has utilized APS for the autonomous operation of heterogeneous constellations of Low Earth Orbit (LEO) satellites with DARPA and AFRL, heterogeneous swarms of unmanned underwater/surface/aerial vehicles (UUVs/USVs/UAVs) with the Navy, and heterogeneous swarms of rovers, satellites, and atmospheric vehicles for robotic Mars exploration with NASA.
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