LoRa-Based Low-Cost Nanosatellite for Emerging Communication Networks in Complex Scenarios

in Aerospace (2023)

Wireless broadband coverage has reached 95% worldwide. However, its trend is expected to stay the same in the following years, presenting challenges for scenarios such as remote villages and their ... [more ▼]

Wireless broadband coverage has reached 95% worldwide. However, its trend is expected to stay the same in the following years, presenting challenges for scenarios such as remote villages and their surrounding environments. Inaccessibility to these areas for installing terrestrial base stations is the main challenge to bridge the connectivity gap. In addition, there are emergencies, for instance, earthquakes or war areas, that require a fast communication reaction by developing networks that are less susceptible to disruption. Therefore, we propose a low-cost, green-based nanosatellite system to provide complete coverage in hard-to-reach areas using long-range communication. The system comprises a pilot station, a base station, and a CubeSat with sensor data collector capabilities acting as a repeater. Our system can be built within hours with a 3D printer using common material, providing a flexible environment where components can be replaced freely according to user requirements, such as sensors and communication protocols. The experiments are performed in Spain by two test sets validating the communication among all components, with RSSI values below -148 dBm and the longest distance above 14 km. We highlight the reduction in the environmental impact of this proposal using a balloon-based launch platform that contributes to sustainable development. [less ▲]

Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors

in Aerospace (2018), 5(3),

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor ... [more ▼]

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack. [less ▲]