Giancarmine Fasano

TL;DR: A review of state-of-the-art techniques and algorithms developed in the last decades for cooperative and uncooperative pose determination by processing data provided by electro-optical sensors is presented.

TL;DR: In order to evaluate the performance of the collision avoidance system, numerical simulations have been performed taking into account the obstacle detection sensors’ accuracy, unmanned aircraft’s and intruder's flight dynamics, navigation system accuracy and latencies, and collision avoidance logic.

TL;DR: A three dimensional approach is pursued in which the point cloud generated by a LIDAR is exploited for pose estimation, and results demonstrate algorithm capability of operating with sparse point clouds and large pose variations, while achieving sub-degree and sub-centimeter accuracy in relative attitude and position, respectively.

TL;DR: This tutorial outlines and reviews the substantial breadth of SAA architectures, technologies, and algorithms, and concludes with a summary of the regulatory and technical issues that continue to challenge the progress on SAA, as a key component of reliable UAS operation in civil aviation authorities (CAAs) around the world.

TL;DR: This paper presents the performance assessment of innovative model-based algorithms developed for pose estimation of uncooperative targets by processing sparse three-dimensional point clouds and demonstrates algorithms' effectiveness over a wide range of relative pose conditions and dealing with targets of variable size and shape.