Real Time UAV Altitude, Attitude and Motion Estimation form Hybrid Stereovision

International audienceKnowledge of altitude, attitude and motion is essential for an Unmanned Aerial Vehicle during crit- ical maneuvers such as landing and take-off. In this paper we present a hybrid stereoscopic rig composed of a fisheye and a perspective camera for vision-based navigation. In contrast to classical stereoscopic systems based on feature matching, we propose methods which avoid matching between hybrid views. A plane-sweeping approach is proposed for estimating altitude and de- tecting the ground plane. Rotation and translation are then estimated by decoupling: the fisheye camera con- tributes to evaluating attitude, while the perspective camera contributes to estimating the scale of the trans- lation. The motion can be estimated robustly at the scale, thanks to the knowledge of the altitude. We propose a robust, real-time, accurate, exclusively vision-based approach with an embedded C++ implementation. Although this approach removes the need for any non-visual sensors, it can also be coupled with an Inertial Measurement Unit

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

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

Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Development and Validation of a LiDAR Scanner for 3D Evaluation of Soil Vegetal Coverage

Water and wind erosion are serious problems due to the loss of soil productivity. The coverage of soil, by means of cover crops or crops residues, is an effective tool to prevent wind and water erosion. The soil coverage could curb wind on the surface, avoid water runoff and reduce direct soil evaporation. Residue spatial distribution is the main factor to successful soil protection. The current work presents details of a prototype, design and validation as a measuring instrument to sense the height of vegetal crop residues based on a short-ranged laser distance sensor (LiDAR) and a computer numerical control (CNC) mechanism. The results obtained in this work showed a high level of confidence to estimate the height and composition of soil vegetal coverage.Fil: Micheletto, Matías Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Zubiaga, Luciano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Galantini, Juan Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Cantamutto, Miguel Ángel. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Orozco, Javier Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

Autonomous vehicle guidance in unknown environments

Gaining from significant advances in their performance granted by technological evolution, Autonomous Vehicles are rapidly increasing the number of fields of possible and effective applications. From operations in hostile, dangerous environments (military use in removing unexploded projectiles, survey of nuclear power and chemical industrial plants following accidents) to repetitive 24h tasks (border surveillance), from power-multipliers helping in production to less exotic commercial application in household activities (cleaning robots as consumer electronics products), the combination of autonomy and motion offers nowadays impressive options. In fact, an autonomous vehicle can be completed by a number of sensors, actuators, devices making it able to exploit a quite large number of tasks. However, in order to successfully attain these results, the vehicle should be capable to navigate its path in different, sometimes unknown environments. This is the goal of this dissertation: to analyze and - mainly - to propose a suitable solution for the guidance of autonomous vehicles. The frame in which this research takes its steps is the activity carried on at the Guidance and Navigation Lab of Sapienza – Università di Roma, hosted at the School of Aerospace Engineering. Indeed, the solution proposed has an intrinsic, while not limiting, bias towards possible space applications, that will become obvious in some of the following content. A second bias dictated by the Guidance and Navigation Lab activities is represented by the choice of a sample platform. In fact, it would be difficult to perform a meaningful study keeping it a very general level, independent on the characteristics of the targeted kind of vehicle: it is easy to see from the rough list of applications cited above that these characteristics are extremely varied. The Lab hosted – even before the beginning of this thesis activity – a simple, home-designed and manufactured model of a small, yet performing enough autonomous vehicle, called RAGNO (standing for Rover for Autonomous Guidance Navigation and Observation): it was an obvious choice to select that rover as the reference platform to identify solutions for guidance, and to use it, cooperating to its improvement, for the test activities which should be considered as mandatory in this kind of thesis work to validate the suggested approaches. The draft of the thesis includes four main chapters, plus introduction, final remarks and future perspectives, and the list of references. The first chapter (“Autonomous Guidance Exploiting Stereoscopic Vision”) investigates in detail the technique which has been deemed as the most interesting for small vehicles. The current availability of low cost, high performance cameras suggests the adoption of the stereoscopic vision as a quite effective technique, also capable to making available to remote crew a view of the scenario quite similar to the one humans would have. Several advanced image analysis techniques have been investigated for the extraction of the features from left- and right-eye images, with SURF and BRISK algorithm being selected as the most promising one. In short, SURF is a blob detector with an associated descriptor of 64 elements, where the generic feature is extracted by applying sequential box filters to the surrounding area. The features are then localized in the point of the image where the determinant of the Hessian matrix H(x,y) is maximum. The descriptor vector is than determined by calculating the Haar wavelet response in a sampling pattern centered in the feature. BRISK is instead a corner detector with an associated binary descriptor of 512 bit. The generic feature is identified as the brightest point in a sampling circular area of N pixels while the descriptor vector is calculated by computing the brightness gradient of each of the N(N-1)/2 pairs of sampling points. Once left and right features have been extracted, their descriptors are compared in order to determine the corresponding pairs. The matching criterion consists in seeking for the two descriptors for which their relative distance (Euclidean norm for SURF, Hamming distance for BRISK) is minimum. The matching process is computationally expensive: to reduce the required time the thesis successfully explored the theory of the epipolar geometry, based on the geometric constraint existing between the left and right projection of the scene point P, and indeed limiting the space to be searched. Overall, the selected techniques require between 200 and 300 ms on a 2.4GHz clock CPU for the feature extraction and matching in a single (left+right) capture, making it a feasible solution for slow motion vehicles. Once matching phase has been finalized, a disparity map can be prepared highlighting the position of the identified objects, and by means of a triangulation (the baseline between the two cameras is known, the size of the targeted object is measured in pixels in both images) the position and distance of the obstacles can be obtained. The second chapter (“A Vehicle Prototype and its Guidance System”) is devoted to the implementation of the stereoscopic vision onboard a small test vehicle, which is the previously cited RAGNO rover. Indeed, a description of the vehicle – the chassis, the propulsion system with four electric motors empowering the wheels, the good roadside performance attainable, the commanding options – either fully autonomous, partly autonomous with remote monitoring, or fully remotely controlled via TCP/IP on mobile networks - is included first, with a focus on different sensors that, depending on the scenario, can integrate the stereoscopic vision system. The intelligence-side of guidance subsystem, exploiting the navigation information provided by the camera, is then detailed. Two guidance techniques have been studied and implemented to identify the optimal trajectory in a field with scattered obstacles: the artificial potential guidance, based on the Lyapunov approach, and the A-star algorithm, looking for the minimum of a cost function built on graphs joining the cells of a mesh over-imposed to the scenario. Performance of the two techniques are assessed for two specific test-cases, and the possibility of unstable behavior of the artificial potential guidance, bouncing among local minima, has been highlighted. Overall, A-star guidance is the suggested solution in terms of time, cost and reliability. Notice that, withstanding the noise affecting information from sensors, an estimation process based on Kalman filtering has been also included in the process to improve the smoothness of the targeted trajectory. The third chapter (“Examples of Possible Missions and Applications”) reports two experimental campaigns adopting RAGNO for the detection of dangerous gases. In the first one, the rover accommodates a specific sensor, and autonomously moves in open fields, avoiding possible obstacles, to exploit measurements at given time intervals. The same configuration for RAGNO is also used in the second campaign: this time, however, the path of the rover is autonomously computed on the basis of the way points communicated by a drone which is flying above the area of measurements and identifies possible targets of interest. The fourth chapter (“Guidance of Fleet of Autonomous Vehicles ”) stresses this successful idea of fleet of vehicles, and numerically investigates by algorithms purposely written in Matlab the performance of a simple swarm of two rovers exploring an unknown scenario, pretending – as an example - to represent a case of planetary surface exploration. The awareness of the surrounding environment is dictated by the characteristics of the sensors accommodated onboard, which have been assumed on the basis of the experience gained with the material of previous chapter. Moreover, the communication issues that would likely affect real world cases are included in the scheme by the possibility to model the comm link, and by running the simulation in a multi-task configuration where the two rovers are assigned to two different computer processes, each of them having a different TCP/IP address with a behavior actually depending on the flow of information received form the other explorer. Even if at a simulation-level only, it is deemed that such a final step collects different aspects investigated during the PhD period, with feasible sensors’ characteristics (obviously focusing on stereoscopic vision), guidance technique, coordination among autonomous agents and possible interesting application cases