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Spacecraft Rendezvous Guidance in Cluttered Dynamical Environments via Extreme Learning Machines

Completed TRL 3 (started at 2, targeting 3)

Description

DeepAnalytX, Inc. proposes to investigate a new approach to perform real-time, closed-loop optimal and robust rendezvous guidance in space environments comprising a potentially large number of spacecraft. More specifically, we propose to research and develop an advanced guidance system that is able to learn and track a fuel-efficient, collision-avoidance velocity vector field thus enabling safe, robust and effective relative motion guidance for autonomous rendezvous in space dynamical environments cluttered with cooperative and non-cooperative resident space objects. The guidance approach implements the next generation of Artificial Potential Functions Guidance (APFG) using an innovative combination of optimal control methods and Extreme Learning Machines (ELMs). Phase I of this proposal seeks to develop and demonstrate software for autonomous rendezvous guidance using a combination of optimal control theory and new machine learning approaches. The key critical innovation is to use ELM algorithms that enable a dramatic training speed-up of many order of magnitude. Phase I development will directly support NASA mission needs for autonomous guidance algorithms in relative motion that execute in real-time autonomous collision avoidance in a fuel efficient fashion with the goal of reducing operational risks (i.e.. increase safety) and operational costs.

Benefits

- Autonomous Rendezvous and Docking for Earth-based and Deep-Space Missions: The proposed FOCA-ELM algorithm may enable safe and accurate guidance for relative motion in space environments that are potentially cluttered with cooperative and non-cooperative RSOs. Thus, such algorithms can be employed for applications involving rendezvous and docking operations. - Asteroid and Comet exploration: Solution architectures that address growing capabilities and capacity for precise and safe close-proximity operations (e.g. landing, hovering Touach-And-Go) for robotic and crewed missions.

Advanced guidance and control technologies for relative motion in space will support continuity of operations and autonomy for multiple tactical and/or strategic DoD and Commercial missions. The latter include 1) In-Orbit Spacecraft Servicing and 2) In-Orbit Space Situational Awareness.

Details

Technology areaGN&C > Guidance and Targeting Algorithms > Guidance Algorithms
ProgramSmall Business Innovation Research/Small Business Tech Transfer (SBIR/STTR)
Lead organizationDeepAnalytX, Tucson, AZ
Start date2017-06-09
End date2017-12-08

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