Acceleration-Aware Path Planning with Waypoints

Abstract

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.

Inverse Airborne Optical Sectioning

“…With Airborne Optical Sectioning (AOS) [48][49][50][51][52][53][54][55][56][57][58][59][60], we introduced an optical synthetic aperture imaging technique that captures an unstructured light field with an aircraft, such as a drone. We utilized manually, automatically [48][49][50][51][52][53][54][55][56]58,59], or fully autonomously [57] operated camera drones that sample multispectral (RGB and thermal) images within a certain (synthetic aperture) area above occluding vegetation (such as forest) and combined their signals computationally to remove occlusion. The outcome is a widely occlusion-free integral image of the ground, revealing details of registered targets while unregistered occluders above the ground, such as trunks, branches or leaves disappear in strong defocus.…”