dc.contributor.author |
Shao, Elly |
|
dc.contributor.author |
Byon, Amos |
|
dc.contributor.author |
Davies, Chris |
|
dc.contributor.author |
Davis, Evan |
|
dc.contributor.author |
Knight, Russell |
|
dc.contributor.author |
Lewellen, Garett |
|
dc.contributor.author |
Trowbridge, Michael |
|
dc.contributor.author |
Chien, Steve |
|
dc.date.accessioned |
2020-05-07T00:59:20Z |
|
dc.date.available |
2020-05-07T00:59:20Z |
|
dc.date.issued |
2018-06-24 |
|
dc.identifier.citation |
International Conference on Automated Planning and Scheduling (ICAPS) 2018, Delft, The Netherlands, June 24 - 29, 2018 |
en_US |
dc.identifier.clearanceno |
18-2435 |
|
dc.identifier.uri |
http://hdl.handle.net/2014/48302 |
|
dc.description.abstract |
Existing algorithms for Agile Earth Observing Satellites((Lemaitre et al. 2002)) were largely created for 1D line sensors that acquire images in linear swaths. However, imaging satellites increasingly use 2D framing sensors (cameras) that capture discrete rectangular images. We describe tiling step-stare approaches that are more suited to rectangular image footprints than are 1D swath-based algorithms. Optimal area planning for these 2D framing instruments is an NPcomplete problem and intractable for large areas, so we present four approximation algorithms. Strategies are compared against a prior 2D framing instrument algorithm (Knight 2014) in three computational experiments. The impact of observer agility on schedule makespan is examined. Makespans vary more as observer agility decreases toward a critical point, then vary less after the critical point, suggesting a possible problem phase transition. |
en_US |
dc.description.sponsorship |
NASA/JPL |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2018 |
en_US |
dc.title |
Area Coverage Planning with 3-axis Steerable, 2D Framing Sensors |
en_US |
dc.type |
Preprint |
en_US |