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Article

Acceleration-Aware Path Planning with Waypoints

Institute of Computer Graphics, Johannes Kepler University Linz, 4040 Linz, Austria
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Author to whom correspondence should be addressed.
Academic Editors: Diego González-Aguilera and Pablo Rodríguez-Gonzálvez
Drones 2021, 5(4), 143; https://doi.org/10.3390/drones5040143
Received: 29 October 2021 / Revised: 23 November 2021 / Accepted: 26 November 2021 / Published: 27 November 2021
(This article belongs to the Collection Feature Papers of Drones)
In this article we demonstrate that acceleration and deceleration of direction-turning drones at waypoints have a significant influence to path planning which is important to be considered for time-critical applications, such as drone-supported search and rescue. We present a new path planning approach that takes acceleration and deceleration into account. It follows a local gradient ascend strategy which locally minimizes turns while maximizing search probability accumulation. Our approach outperforms classic coverage-based path planning algorithms, such as spiral- and grid-search, as well as potential field methods that consider search probability distributions. We apply this method in the context of autonomous search and rescue drones and in combination with a novel synthetic aperture imaging technique, called Airborne Optical Sectioning (AOS), which removes occlusion of vegetation and forest in real-time. View Full-Text
Keywords: search and rescue; autonomous drones; path planning; acceleration; deceleration search and rescue; autonomous drones; path planning; acceleration; deceleration
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MDPI and ACS Style

Ortner, R.; Kurmi, I.; Bimber, O. Acceleration-Aware Path Planning with Waypoints. Drones 2021, 5, 143. https://doi.org/10.3390/drones5040143

AMA Style

Ortner R, Kurmi I, Bimber O. Acceleration-Aware Path Planning with Waypoints. Drones. 2021; 5(4):143. https://doi.org/10.3390/drones5040143

Chicago/Turabian Style

Ortner, Rudolf, Indrajit Kurmi, and Oliver Bimber. 2021. "Acceleration-Aware Path Planning with Waypoints" Drones 5, no. 4: 143. https://doi.org/10.3390/drones5040143

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