Recently, UAV usage spread to various areas of life. In many cases, UAVs carry expensive equipment onboard. Most of the aircraft damage occurs during the landing due to hard landings. To decrease the number of such situations landing aid systems are being developed. Since most of those systems need special airfield infrastructure, in this project a simple and low-cost system is proposed. This paper provides an overview of the UAV landing aid systems and a concept of the computer vision-based landing aid system. The proposed solution uses ArUco markers as reference points during the landing. By using marker pose estimation algorithm it is possible to determine the height of the flight during the touchdown with high accuracy. The fusion of the data acquired from the inertial sensors generates precise information about the path of the approach of the UAV. In addition, markers placed across the airstrip may be used to navigate during taxing. The developed solution has been tested for accuracy of position determination and for an influence of marker size on accuracy and measurement divergence.

The aim of this paper is to highlight how the employment of Light Detection and Ranging (LiDAR) technique can enhance greatly the performance and reliability of many monitoring systems applied to the Earth Observation (EO) and Environmental Monitoring. A short presentation of LiDAR systems, underlying their peculiarities, is first given. References to some review papers are highlighted, as they can be regarded as useful guidelines for researchers interested in using LiDARs. Two case studies are then presented and discussed, based on the use of 2D and 3D LiDAR data. Some considerations are done on the performance achieved through the use of LiDAR data combined with data from other sources. The case studies show how the LiDAR-based systems, combined with optical Very High Resolution (VHR) data, succeed in improving the analysis and monitoring of specific areas of interest, specifically how LiDAR data help in exploring external environment and extracting building features from urban areas. Moreover the discussed Case Studies demonstrate that the use of the LiDAR data, even with a low density of points, allows the development of an automatic procedure for accurate building features extraction, through object-oriented classification techniques, therefore by underlying the importance that even simple LiDAR-based systems play in EO and Environmental Monitoring.

This paper presents a conception of an indoor positioning system for an unmanned aerial vehicle (UAV). The measurement of magnetic field is a main source of information required to estimate a position of the platform. It is a parameter which can be measured with affordable sensors and is easy to obtain. In order to use acquired data, a magnetic field map of the specified environment should be previously determined. Thus, a few ideas of using this information were elaborated. First of all, dedicated hardware had to be designed to implement the method. In this process, a multipurpose measurement system was developed. The measurement system consists of three axis digital magnetometers and battery powered microprocessor system with SD memory card and LCD display. The module was installed on the specially designed chassis that enable testing on 3 different heights. The verification tests were performed in designated room, where permanent magnets were used to modify local magnetic field that could work as beacons.

Nowadays, unmanned aerial systems (UASs) find application in several fields [1], such as agriculture, environmental monitoring, energy, geology, and archaeology [2], and the list is continually growing. Light vertical takeoff and landing-remotely piloted aircraft systems, often called generic UASs, are the most used platforms due to their low weight, low size, and low cost [1]. This trend is due to the integration on the UAS of high-performance processors, sensors, and actuators with very low power consumption.

This paper describes the development process of the quadcopter-based unmanned flying platform, designed for testing and experimentation purposes. The project features custom-made hardware, which includes the prototype quadcopter frame and the flight controller, and software solutions, such as control loop setup. The article specifies the controller tuning used for the initialization of the flight stabilization system and presents the final results of the quadcopter performance evaluation.