Continuous-time trajectory optimization for online UAV replanning
Helen Oleynikova, Michael Burri, Zachary Taylor, Juan Nieto, Roland Siegwart, Enric Galceran
Abstract
Multirotor unmanned aerial vehicles (UAVs) are rapidly gaining popularity for many applications. However, safe operation in partially unknown, unstructured environments remains an open question. In this paper, we present a continuous-time trajectory optimization method for real-time collision avoidance on multirotor UAVs. We then propose a system where this motion planning method is used as a local replanner, that runs at a high rate to continuously recompute safe trajectories as the robot gains information about its environment. We validate our approach by comparing against existing methods and demonstrate the complete system avoiding obstacles on a multirotor UAV platform.
BibTeX
@inproceedings{iros2016_continuoustimetr,
title = {Continuous-time trajectory optimization for online UAV replanning},
author = {Helen Oleynikova and Michael Burri and Zachary Taylor and Juan Nieto and Roland Siegwart and Enric Galceran},
booktitle = {IROS 2016},
year = {2016}
}