Exploiting Solar Energy during an Aerial Mapping Mission on a Lightweight UAV

In this study, we present options for extending the endurance of a lightweight unmanned aerial vehicle (UAV), along with their advantages and disadvantages. We present a developed solution based on the use of gallium–arsenide (GaAs) solar modules installed on a UAV and connected to a custom-made maximum power point tracker (MPPT) with an integrated perturb and observe (P&O) algorithm. The mathematical behavior required to calculate the electrical energy production from solar energy on the UAV from known UAV angles of rotation, the position of the sun in the sky, solar irradiance measurements, the solar module area and the solar modules efficiency is presented. A comparison of the calculated and actual measured electrical energy production results during an aerial mapping mission is presented. We perform a number of aerial mapping mission flights and the experimental results confirm an energy efficiency value of more than 96.27% for the MPPT and extended flight endurance by up to 21.25%. In addition, onboard measurements and other data captured during flights confirm the proposed electrical energy production calculation.

A Rigorous Observation Model for the Risley Prism-Based Livox Mid-40 Lidar Sensor

Modern lidar sensors are continuing to decrease in size, weight, and cost, but the demand for fast, abundant, and high-accuracy lidar observations is only increasing. The Livox Mid-40 lidar sensor was designed for use within sense-and-avoid navigation systems for autonomous vehicles, but has also found adoption within aerial mapping systems. In order to characterize the overall quality of the point clouds from the Mid-40 sensor and enable sensor calibration, a rigorous model of the sensor’s raw observations is needed. This paper presents the development of an angular observation model for the Mid-40 sensor, and its application within an extended Kalman filter that uses the sensor’s data to estimate the model’s operating parameters, systematic errors, and the instantaneous prism rotation angles for the Risley prism optical steering mechanism. The analysis suggests that the Mid-40’s angular observations are more accurate than the specifications provided by the manufacturer. Additionally, it is shown that the prism rotation angles can be used within a planar constrained least-squares adjustment to theoretically improve the accuracy of the angular observations of the Mid-40 sensor.

3D CONTENT GENERATION USING HYBRID AERIAL SENSOR DATA

In aerial data acquisition a new era started with the introduction of the first real hybrid sensor systems, like the Leica CityMapper-2. Hybrid in this context means the combination of an (oblique) camera system with a topographic LiDAR into an integrated aerial mapping system. By combining these complimentary sub-systems into one system the weaknesses of the one system could be compensated by using the alternative data source. An example is the mapping of low-light urban canyons, where image-based systems mostly produce unreliable results. For an LiDAR sensor the geometrical reconstruction of these areas is straight forward and leads to accurate results. The paper gives a detailed overview over the development and technical characteristics of hybrid sensor systems. The process of data acquisition is discussed and strategies for hybrid urban mapping are proposed. A hybrid sensor alone is just a part of the whole procedure to generate 3D content. As important as the senor itself is the workflow to generate the products. Here again a hybrid approach, with the processing of all datasets in one environment, is discussed. Special attention is paid to the hybrid orientation of the data and the integrated generation of base and enhanced products. The paper is rounded off by the discussion of the advantage of LiDAR data for the 3D Mesh generation for urban modelling.

Aerial Mapping of Odorous Gases in a Wastewater Treatment Plant Using a Small Drone

Wastewater treatment plants (WWTPs) are sources of greenhouse gases, hazardous air pollutants and offensive odors. These emissions can have negative repercussions in and around the plant, degrading the quality of life of surrounding neighborhoods, damaging the environment, and reducing employee’s overall job satisfaction. Current monitoring methodologies based on fixed gas detectors and sporadic olfactometric measurements (human panels) do not allow for an accurate spatial representation of such emissions. In this paper we use a small drone equipped with an array of electrochemical and metal oxide (MOX) sensors for mapping odorous gases in a mid-sized WWTP. An innovative sampling system based on two (10 m long) flexible tubes hanging from the drone allowed near-source sampling from a safe distance with negligible influence from the downwash of the drone’s propellers. The proposed platform is very convenient for monitoring hard-to-reach emission sources, such as the plant’s deodorization chimney, which turned out to be responsible for the strongest odor emissions. The geo-localized measurements visualized in the form of a two-dimensional (2D) gas concentration map revealed the main emission hotspots where abatement solutions were needed. A principal component analysis (PCA) of the multivariate sensor signals suggests that the proposed system can also be used to trace which emission source is responsible for a certain measurement.

A review on drones controlled in real-time

This paper presents related literature review on drones or unmanned aerial vehicles that are controlled in real-time. Systems in real-time control create more deterministic response such that tasks are guaranteed to be completed within a specified time. This system characteristic is very much desirable for drones that are now required to perform more sophisticated tasks. The reviewed materials presented were chosen to highlight drones that are controlled in real time, and to include technologies used in different applications of drones. Progress has been made in the development of highly maneuverable drones for applications such as monitoring, aerial mapping, military combat, agriculture, etc. The control of such highly maneuverable vehicles presents challenges such as real-time response, workload management, and complex control. This paper endeavours to discuss real-time aspects of drones control as well as possible implementation of real-time flight control system to enhance drones performance.

Surface modelling of a unique heritage object: use of UAV combined with camera and LiDAR for mound inspection

Nowadays, the use of Unmanned Aerial Vehicle flying at a low altitude in conjunction with photogrammetric and LiDAR technologies allows to collect images of very high-resolution to generate dense points cloud and to simulate geospatial data of territories. The technology used in experimental research contains reconstruction of topography of surface with historical structure, observing the recreational infrastructure, obtaining geographic information for users who are involved in preservation and inspection of such unique cultural/ heritage object as are mounds in Lithuania. In order to get reliable aerial mapping products of preserved unique heritage object, such photogrammetric/ GIS procedures were performed: UAV flight for taking images with the camera; scanning surface by LiDAR simultaneously; processing of image data, 3D modelling and generation of orthophoto. Evaluation of images processing results shows that the accuracy of surface modelling by the use of UAV photogrammetry method satisfied requirements – mean RMSE equal to 0.031 m. The scanning surface by LiDAR from low altitude is advisable, relief representation of experimental area was obtained with mean accuracy up to 0.050 m. Aerial mapping by the use of UAV requires to specify appropriate ground sample distance (GSD) that is important for reducing number of images and time duration for modelling of area. Experiment shows that specified GSD of 1.7 cm is not reasonable, GSD size increased by 1.5 time would be applicable. The use of different software in addition for DSM visualization and analysis is redundant action.