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Spacecraft Swarm Coordination and Planning Tool

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX16CP26P
Agency Tracking Number: 150252
Amount: $124,853.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: T4.03
Solicitation Number: N/A
Timeline
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-06-10
Award End Date (Contract End Date): 2017-06-09
Small Business Information
90 Broadway, 11th Floor
Cambridge, MA 02142-1050
United States
DUNS: 000000000
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Sachin Jain
 Sr. GNC Engineer
 (617) 229-6812
 jain.sachin@aurora.aero
Business Contact
 Scott Hart
Title: Site Controller
Phone: (617) 500-4892
Email: hart.scott@aurora.aero
Research Institution
 Massachusetts Institute of Technology
 Michael Corcoran
 
77 Massachusetts Avenue
Cambridge, MA 02139-4301
United States

 (617) 253-3906
 Domestic Nonprofit Research Organization
Abstract

Fractionated spacecraft architectures to distribute mission performance from a single, monolithic satellite across large number of smaller spacecraft, for missions like close proximity inspection, sparse aperture arrays, robotic assembly, servicing, refueling, etc., can enable higher mission capability, reconfigurability and robustness. This distributed satellite architecture, with large numbers of agents, comes at the cost of extensive mission planning and computational complexity, and greater risk of collisions. As mission profiles scale up to hundreds of agents, there is an exponential increase in the system complexity needed to both plan and control satellite swarm activity and ensure it operates safely in the environment densely populated by other agents.

Aurora Flight Sciences and the MIT Space Systems Lab propose a novel and comprehensive swarm coordination and planning tool that will allow ground-based operators to provide high level mission goals, and observe and re-direct swarms of spacecraft in LEO as the autonomy dynamically plans and executes complex multi-agent missions. The proposed effort combines elements of autonomous, dynamic, multi-vehicle coordination and path planning to meet mission objectives, facilitates close-proximity operations by integrating sensors and software for collision detection and avoidance, and allows high-level human-in-the-loop control of critical mission performance by implementing a Human-Swarm interface.

Phase I focuses on developing and simulating discrete elements of the conceptual tool, leveraging powerful task allocation and path planning algorithms that Aurora has developed over the past several years, coupled with MIT's autonomous collision detection & avoidance and human swarm interfaces. In Phase II we will integrate the modules with a space mission analysis tool and demonstrate performance of key technologies on the SPHERES hardware testbed.

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

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