Abstract
This paper describes an energy-aware, airborne, dynamic data-driven application systems for persistent sensing in complex atmospheric conditions. The work combines i.) new onboard and remote real-time, wind sensing capabilities; ii.) online models for planning based on Gaussian processes for onboard data and dynamic atmospheric models that assimilate Doppler radar data; and iii.) a hierarchical guidance and control framework with algorithms that can adapt to environmental, sensing, and computational resources. The novel aspects of this work include real-time synthesis of multiple Doppler radar data into wind field measurements; creation of atmospheric models for online planning that can be run inside guidance loops; guidance algorithms based on stochastic dynamic programming and ordered upwind methods that can adapt planning horizons, cost function approximations, and mesh representations of the environment; and throttling algorithms that manage the adaptation of the models and guidance algorithms in response to computational resources.
Original language | English |
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Pages (from-to) | 2008-2017 |
Number of pages | 10 |
Journal | Procedia Computer Science |
Volume | 18 |
DOIs | |
State | Published - 2013 |
Event | 13th Annual International Conference on Computational Science, ICCS 2013 - Barcelona, Spain Duration: Jun 5 2013 → Jun 7 2013 |
Keywords
- Atmospheric models
- Dynamic data-driven application system
- Planning and control
- Unmanned aircraft system