Abstract | ||
---|---|---|
The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat-21 constellation of three spacecraft scheduled for launch in 2004. 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 a hybrid multi-layer control architecture to enable a virtual spacecraft science agent. We also describe our working software prototype and preparations for flight. |
Year | DOI | Venue |
---|---|---|
2002 | 10.1145/544862.544880 | AAMAS |
Keywords | Field | DocType |
machine learning,autonomy,pattern recognition | Architecture,Space Science,Computer science,Real-time computing,Retargeting,Constellation,Software,Control reconfiguration,Telecommunications link,Spacecraft | Conference |
ISBN | Citations | PageRank |
1-58113-480-0 | 15 | 1.51 |
References | Authors | |
10 | 15 |
Name | Order | Citations | PageRank |
---|---|---|---|
Steve Chien | 1 | 286 | 43.51 |
Rob Sherwood | 2 | 1462 | 128.08 |
Gregg Rabideau | 3 | 244 | 29.61 |
Rebecca Castano | 4 | 102 | 14.05 |
Ashley Davies | 5 | 56 | 8.56 |
Michael C. Burl | 6 | 445 | 106.47 |
Russell Knight | 7 | 85 | 6.86 |
Timothy M. Stough | 8 | 21 | 3.23 |
Joseph Roden | 9 | 15 | 1.51 |
Paul Zetocha | 10 | 16 | 3.00 |
Ross Wainwright | 11 | 19 | 4.09 |
Pete Klupar | 12 | 15 | 1.51 |
Jim Van Gaasbeck | 13 | 16 | 1.99 |
Pat Cappelaere | 14 | 22 | 2.98 |
Dean Oswald | 15 | 15 | 1.51 |