@inproceedings{shao_spark2018_coverage,
 abstract = {Existing algorithms for Agile Earth Observing Satellites 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 NP-complete 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.},
 address = {Delft, Netherlands},
 author = { Elly Shao and Amos Byon and Chris Davies and Evan Davis and Russell Knight and Garett Lewellen and Michael Trowbridge and Steve Chien},
 booktitle = {Scheduling and Planning Applications Workshop , International Conference on Automated Planning and Scheduling (ICAPS SPARK 2018)},
 clearance = {CL#18-2435},
 month = {June},
 project = {EagleEye},
 title = {Area Coverage Planning with 3-axis Steerable, 2D Framing Sensors},
 url = {https://ai.jpl.nasa.gov/public/papers/shao-spark2018-coverage.pdf},
 year = {2018}
}

Existing algorithms for Agile Earth Observing Satellites 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 NP-complete 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.

@inproceedings{lewellen-davies-byon-et-al-IWPSS-2017,
 address = {Pittsburgh, PA},
 author = {Garrett Lewellen and Christopher Davies and Amos Byon and Russell Knight and Elly Shao and Daniel Tran and Michael Trowbridge},
 booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
 clearance = {CL#17-2697},
 month = {June},
 project = {EagleEye},
 title = {A Hybrid Traveling Salesman Problem - Squeaky Wheel Optimization Planner for Earth Observational Scheduling},
 url = {https://ai.jpl.nasa.gov/public/papers/lewellen-iwpss2017-hybrid.pdf},
 year = {2017}
}

@inproceedings{lewellen-trowbridge-shao-et-al-IWPSS-2017,
 address = {Pittsburgh, PA},
 author = {Garrett Lewellen and Michael Trowbridge and Elly Shao and Christopher Davies and Russell Knight},
 booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
 clearance = {CL#17-2530},
 month = {June},
 project = {EagleEye},
 title = {Estimating Time to Image Areas with Steerable 2D Framing Sensors},
 url = {https://ai.jpl.nasa.gov/public/papers/lewellen-iwpss2017-estimating.pdf},
 year = {2017}
}