The autonomous sciencecraft experiment

Author

Sherwood, Rob ; Chien, Steve ; Castano, Rebecca ; Rabideau, Gregg

Author_Institution

Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA

Volume

1

fYear

2003

fDate

March 8-15, 2003

Firstpage

1

Abstract

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in hybrid multi-layer control architecture to enable to virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Keywords

aerospace instrumentation; learning (artificial intelligence); pattern recognition; space communication links; space vehicles; virtual instrumentation; AD 2006; AI technologies; ASE; TechSat 21 constellation; autonomous retargeting; autonomous sciencecraft experiment; earth science; flight environment; goal-based execution; intelligent downlink selection; model-based mode identification; multilayer control architecture; onboard continuous planning; onboard machine learning; pattern recognition; planetary science; science return; space physics; virtual spacecraft science agent; Artificial intelligence; Downlink; Geoscience; Learning systems; Machine learning; Pattern recognition; Physics; Robustness; Space technology; Space vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace Conference, 2003. Proceedings. 2003 IEEE

ISSN

1095-323X

Print_ISBN

0-7803-7651-X

Type

conf

DOI

10.1109/AERO.2003.1235068

Filename

1235068