TY - GEN
T1 - Trajectory Estimation for Geo-Fencing Applications on Small-Size Fixed-Wing UAVs
AU - Theile, Mirco
AU - Yu, Simon
AU - Dantsker, Or D.
AU - Caccamo, Marco
N1 - Funding Information:
The material presented in this paper is based upon work supported by the National Science Foundation (NSF) under grant number CNS-1646383. Marco Caccamo was also supported by an Alexander von Humboldt Professorship endowed by the German Federal Ministry of Education and Research. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the NSF.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - The steadily increasing popularity of Unmanned Aerial Vehicles (UAVs) is creating new opportunities in diverse fields of technology and business. However, this increase of popularity also raises safety concerns. To tackle the primary concern of keeping the UAV inside a designated region, a novel trajectory estimation algorithm for geo-fencing applications is proposed. We derive the Beta-Trajectory that takes into account constraints in curvature as well as constraints in the change of curvature which is bounded by the maximum roll-rate of the aircraft. We incorporate the Beta-Trajectory into a geo-fencing algorithm. By using our open-source uavAP autopilot, the applicability and necessity of accurate trajectory estimation algorithms for geo-fencing applications are shown on small fixed-wing aircraft. The model and algorithm are validated in high-fidelity simulations as well as in real flight testing.
AB - The steadily increasing popularity of Unmanned Aerial Vehicles (UAVs) is creating new opportunities in diverse fields of technology and business. However, this increase of popularity also raises safety concerns. To tackle the primary concern of keeping the UAV inside a designated region, a novel trajectory estimation algorithm for geo-fencing applications is proposed. We derive the Beta-Trajectory that takes into account constraints in curvature as well as constraints in the change of curvature which is bounded by the maximum roll-rate of the aircraft. We incorporate the Beta-Trajectory into a geo-fencing algorithm. By using our open-source uavAP autopilot, the applicability and necessity of accurate trajectory estimation algorithms for geo-fencing applications are shown on small fixed-wing aircraft. The model and algorithm are validated in high-fidelity simulations as well as in real flight testing.
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U2 - 10.1109/IROS40897.2019.8967579
DO - 10.1109/IROS40897.2019.8967579
M3 - Conference contribution
AN - SCOPUS:85076468132
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 1971
EP - 1977
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Y2 - 3 November 2019 through 8 November 2019
ER -