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Microgravity Environment Autonomy for Robotic Spacecraft (MEARS)

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC22PB134
Agency Tracking Number: 221810
Amount: $149,829.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: T4
Solicitation Number: STTR_22_P1
Timeline
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-07-20
Award End Date (Contract End Date): 2023-08-25
Small Business Information
7852 Walker Drive
Greenbelt, MD 20770-3208
United States
DUNS: 110592016
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Kenneth Center
 (240) 391-3310
 ken.center@orbitlogic.com
Business Contact
 Kenneth Center
Phone: (240) 391-3310
Email: ken.center@orbitlogic.com
Research Institution
 University of Dayton Research Institute
 
300 College Park
Dayton, OH 45469-0101
United States

 Nonprofit College or University
Abstract

Orbit Logic is teamed with the University of Dayton Research Institution (UDRI) to develop the Microgravity Environment Autonomy for Robotic Satellites (MEARS) solution. MEARS is an effort to merge existing technology elements associated with robotic asset onboard sensing and perception, autonomous planning and response, and inter-asset communication for coordination ndash; into a high-reliability architecture that leverages the ROS 2 (and the evolving Space ROS) open software projects to facilitate data interaction between modular elements. Orbit Logic is bringing our mature Autonomous Planning System (APS) solution for asset-level resource planning and decentralized planning to accomplish mission-level goals with a team of heterogeneous, networked assets. UDRI is bringing its motion control, trajectory planning and team navigation planning capabilities, which have been realized in their Real-Time Adaptable Autonomy Kernel solution (RT-AAK), components of which can be flexibly built and deployed to CPU, GPU and FPGA-based computing resources. UDRI is employing advanced online learning-enabled model predictive control (MPC) techniques to achieve effective AI/ML capabilities. Both APS and RT-AAK are modular, layered solutions with strong synergy that together will be highly enabling technology for a variety of space robotic applications. The Phase I effort will define a unified architecture combing the technologies, using ROS 2 as the mechanism for standardizing the module interfaces to ensure interoperability. This work will be intentionally aligned with the ongoing work of the Space ROS initiative. Our initial use cases will target robotic team collaborative mission in microgravity environments, notably operations of heterogeneous teams in asteroid fields with initially unknown and highly dynamic objects of interest. UDRIrsquo;s Autonomous Systems Lab, with hardware in the loop and high-fidelity dynamics simulation, will be used for prototype verification and validation.

* Information listed above is at the time of submission. *

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