Abstract
Successful operation of micro aerial vehicles in partially known environments requires globally consistent plans based on incomplete environment models and quick reactions to unknown obstacles by means of real-time planning of collision-free trajectories. In this paper, we propose a complete layered mission and navigation planning system based on coarse prior knowledge and local maps from omnidirectional onboard obstacle perception. We generate trajectories in a multilayered approach: from mission planning to global and local trajectory planning to motion control.
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This work has been supported by grant BE 2556/8 of German Research Foundation (DFG).
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Nieuwenhuisen, M., Behnke, S. (2016). Layered Mission and Path Planning for MAV Navigation with Partial Environment Knowledge. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_23
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DOI: https://doi.org/10.1007/978-3-319-08338-4_23
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