@inproceedings {icaps16-199, track = {Applications Track}, title = {Optimal Scheduling of a Constellation of Earth-Imaging Satellites, for Maximal Data Throughput and Efficient Human Management}, url = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13173}, author = {Sean Augenstein and Alejandra Estanislao and Emmanuel Guere and Sean Blaes}, abstract = {A mixed-integer linear program (MILP) approach to scheduling a large constellation of Earth-imaging satellites is presented. The algorithm optimizes the assignment of imagery collects, image data downlinks, and "health & safety" contacts, generating schedules for all satellites and ground stations in a network. Hardware-driven constraints (e.g., the limited agility of the satellites) and operations-driven constraints (e.g., guaranteeing a minimum contact frequency for each satellite) are both addressed. Of critical importance to the use of this algorithm in real-world operations, it runs fast enough to allow for human operator interaction and repeated rescheduling. This is achieved by a partitioning of the problem into sequential steps for downlink scheduling and image scheduling, with a novel dynamic programming (DP) heuristic providing a stand-in for imaging activity in the MILP when scheduling the downlinks.}, keywords = {} }