Local multiresolution trajectory optimization for micro aerial vehicles employing continuous curvature transitions

Abstract

Complex indoor and outdoor missions for autonomous micro aerial vehicles (MAV) require fast generation of collision-free paths in 3D space. Often not all obstacles in an environment are known prior to the mission execution. Consequently, the ability for replanning during a flight is key for success. Our approach locally optimizes trajectories of grid-based… (More)
DOI: 10.1109/IROS.2016.7759497

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Cite this paper

@article{Nieuwenhuisen2016LocalMT, title={Local multiresolution trajectory optimization for micro aerial vehicles employing continuous curvature transitions}, author={Matthias Nieuwenhuisen and Sven Behnke}, journal={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year={2016}, pages={3219-3224} }