development of a software to optimize and plan the acquisitions from uav and a first application in a post seismic environment

AbstractAn Unmanned Aerial Vehicle (UAV) is an aircraft without a human pilot on board. UAVs allow close-range photogrammetric acquisitions potentially useful for building large-scale cartography and acquisitions of building geometry. This is particularly useful in emergency situations where major accessibility problems limit the possibility of using conventional surveys. Presently, however, flights of this class of UAV are planned based only on the pilot's experience and they often acquire three or more times the number of images needed. This is clearly a time-consuming and autonomy-reducing procedure, which is certainly detrimental when extensive surveys are needed. For this reason new software, to plan the UAV's survey will be illustrated

Multiobjective path planner for UAVs based on genetic algorithms

This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Genetic Algorithms (GA) that obtains a feasible and optimal 3-D path for the UAV. It uses 9 different objective values which are calculated with a realistic model of the UAV and the environment and which are structured with 3 levels of priorities. Our planner works globally offline as well as locally online, which means that the algorithm can recalculate parts of the generated path in order to avoid unexpected risks. Finally, the effectiveness of the solutions given by this planner has been successfully tested against a simulator that contains the complete model of the UAV and the environment

UAV APPLICATION IN POST - SEISMIC ENVIRONMENT

Abstract. On April 6, 2009, an earthquake of 6.3 magnitude struck central Italy with its epicentre near L'Aquila, at 42.3502° N, 13.3762° E. The earthquake damaged 3000 to 11 000 buildings in the medieval city of L'Aquila. Several buildings totally collapsed, 308 people were killed. The post emergency phase till now is just at its beginning step. Conventional surveying techniques using high precision total stations, GNSS receivers and laser scanners for investigations on damaged buildings are always becoming more automated, accurate and operative and even much more fast. Even if these techniques represent instruments of extreme operability there are still many evident limits on their use, especially regarding the survey of both the roofs and the facades of tall buildings or dangerous places, typical on post earthquake situations. So using micro UAVs for surveying in such particular cases, many of these problems can be easily bypassed. In fact, the present work aims on experimenting using multi-rotor micro UAVs, that will allow high quality image capturing on roofs and facades of structures in the old city center of L'Aquila. To obtain actual stereoscopic acquisitions of buildings some conditions on the geometry of acquisition have to be observed, for this reason, taking as a guideline classic flight photogrammetric, a flight planning software was developed. Accurate planning for UAVs acquisitions is very important also considering the reduced autonomy of such vehicles. This can be a strategic point if we want to use UAVs for early damage assessment and also for post event reconstruction planning

Development of a software to plan UAVs stereoscopic flight: An application on post earthquake scenario in L'Aquila city

On April 6, 2009, an earthquake hit the historic center of L'Aquila city, hundreds of victims, thousands of collapses. During the post-emergency a continuous monitoring of all building is crucial in order to guarantee that each structure at least will not worsen its stability until the final reconstruction is completed. So detailed surveying of all building is performed using different geomatic techniques as total stations, land photogrammetry, and laser scanners. Even if all these techniques can perfectly respond to many crucial post hazard needs, there are still many monitoring that cannot be completely carried on with traditional techniques. For these reasons, in this work, the advantages of using multirotor UAVs will be illustrated; UAVs can be fully remote controlled and so the geometry of photogrammetric image acquisition can be imposed. For this task planning of flight is essential so a package was realized to obtain actual photogrammetric stereoscopic acquisitions. © 2013 Springer-Verlag Berlin Heidelberg

Offine/online Optimum Routing of a UAV using Auxiliary Points

This paper presents a method to determine the route of a three-dimensional UAV. Three criteria; the height, the length of flight path and the unauthorized areas are used as the constraints and combined in a fuzzy function as the evaluation function. The article aimed to discover a minimum cost route from source to destination considering the constrains. In this paper a new searching method is proposed, with use of auxiliary points. The auxiliary point method iteratively divides a straight line to two shorter lines with less cost of evaluation function. Implementation results show that the proposed method dramatically decreases the calculations; meanwhile the ight route is sub-optimum

Integrity-Based Path Planning Strategy for Urban Autonomous Vehicular Navigation Using GPS and Cellular Signals

An integrity-based path planning strategy for autonomous ground vehicle (AGV) navigation in urban environments is developed. The vehicle is assumed to navigate by utilizing cellular long-term evolution (LTE) signals in addition to Global Positioning System (GPS) signals. Given a desired destination, an optimal path is calculated, which minimizes a cost function that considers both the horizontal protection level (HPL) and travel distance. The constraints are that (i) the ratio of nodes with faulty signals to the total nodes be lower than a maximum allowable ratio and (ii) the HPLs along each candidate path be lower than the horizontal alert limit (HAL). To predict the faults and HPL before the vehicle is driven, GPS and LTE pseudoranges along the candidate paths are generated utilizing a commercial ray-tracing software and three-dimensional (3D) terrain and building maps. Simulated pseudoranges inform the path planning algorithm about potential biases due to reflections from buildings in urban environments. Simulation results are presented showing that the optimal path produced by the proposed path planning strategy has the minimum average HPL among the candidate paths.Comment: Submitted to ION GNSS+ 202

On Acceleration of Evolutionary Algorithms Taking Advantage of A Posteriori Error Analysis

A variety of important engineering and scientific tasks may be formulated as non-linear, constrained optimization problems. Their solution often demands high computational power. It may be reached by means of appropriate hardware, software or algorithm improvements. The Evolutionary Algorithms (EA) approach to solution of such problems is considered here. The EA are rather slow methods; however, the main advantage of their application is observed in the case of non-convex problems. Particularly high efficiency is demanded in the case of solving large optimization problems. Examples of such problems in engineering include analysis of residual stresses in railroad rails and vehicle wheels, as well as the Physically Based Approximation (PBA) approach to smoothing experimental and/or numerical data. Having in mind such analysis in the future, we focus our current research on the significant EA efficiency increase. Acceleration of the EA is understood here, first of all, as decreasing the total computational time required to solve an optimization problem. Such acceleration may be obtained in various ways. There are at least two gains from the EA acceleration, namely i) saving computational time, and ii) opening a possibility of solving larger optimization problems, than it would be possible with the standard EA. In our recent research we have preliminarily proposed several new speed-up techniques based on simple concepts. In this paper we mainly develop acceleration techniques based on simultaneous solutions averaging well supported by a non-standard application of parallel calculations, and a posteriori solution error analysis. The knowledge about the solution error is used to EA acceleration by means of appropriately modified standard evolutionary operators like selection, crossover, and mutation. Efficiency of the proposed techniques is evaluated using several benchmark tests. These tests indicate significant speed-up of the involved optimization process. Further concepts and improvements are also currently being developed and tested