Progettazione ed analisi di algoritmi di mobilità controllata per reti mesh aeree con vincoli di copertura e persistenza

In questo lavoro di tesi verrà presentata l’implementazione di due algoritmi di Deployment e gestione di uno sciame di dispositivi UAV (Unmanned Aerial Vehicles). L’interesse scientifico su cui si fonda quest'analisi ha origine nelle enormi potenzialità degli UAV che garantiscono un'esplorazione aerea di aree pericolose in contesti di emergenze quali ad esempio scenari post catastrofe. La problematica principale affrontata sarà quella della gestione continuativa dell'area disastrata fornendo un algoritmo di schedulazione della cooperazione degli UAV alternando periodi attivi con quelli di ricarica dei dispositivi.

Methane fluxes and carbonate deposits at eastern Mediterranean cold seeps

High acoustic seafloor-backscatter signals characterize hundreds of patches of methane-derived authigenic carbonates and chemosynthetic communities associated with hydrocarbon seepage on the Nile Deep Sea Fan (NDSF) in the Eastern Mediterranean Sea. During a high-resolution ship-based multibeam survey covering a ~ 225 km**2 large seafloor area in the Central Province of the NDSF we identified 163 high-backscatter patches at water depths between 1500 and 1800 m, and investigated the source, composition, turnover, flux and fate of emitted hydrocarbons. Systematic Parasound single beam echosounder surveys of the water column showed hydroacoustic anomalies (flares), indicative of gas bubble streams, above 8% of the high-backscatter patches. In echosounder records flares disappeared in the water column close to the upper limit of the gas hydrate stability zone located at about 1350 m water depth due to decomposition of gas hydrate skins and subsequent gas dissolution. Visual inspection of three high-backscatter patches demonstrated that sediment cementation has led to the formation of continuous flat pavements of authigenic carbonates typically 100 to 300 m in diameter. Volume estimates, considering results from high-resolution autonomous underwater vehicle (AUV)-based multibeam mapping, were used to calculate the amount of carbonate-bound carbon stored in these slabs. Additionally, the flux of methane bubbles emitted at one high-backscatter patch was estimated (0.23 to 2.3 × 10**6 mol a**-1) by combined AUV flare mapping with visual observations by remotely operated vehicle (ROV). Another high-backscatter patch characterized by single carbonate pieces, which were widely distributed and interspaced with sediments inhabited by thiotrophic, chemosynthetic organisms, was investigated using in situ measurements with a benthic chamber and ex situ sediment core incubation and allowed for estimates of the methane consumption (0.1 to 1 × 10**6 mol a**-1) and dissolved methane flux (2 to 48 × 10**6 mol a**-1). Our comparison of dissolved and gaseous methane fluxes as well as methane-derived carbonate reservoirs demonstrates the need for quantitative assessment of these different methane escape routes and their interaction with the geo-, bio-, and hydrosphere at cold seeps.

Alternatives Linienführungssystem für autonome, fahrerlose Transportsysteme

In modernen Unternehmen zählen fahrerlose Transportsysteme (FTS) zum Stand der Technik. Die am weitesten verbreitete Form solcher Systeme stellen spurgeführte Systeme dar. Durch die jahrzehntelange Entwicklung und den jahrzehntelangen Einsatz gelten solche Systeme als erprobt und robust. Allerdings werden sie, auf Grund minimaler Möglichkeiten auf ihre Umwelt zu reagieren, auch als unflexibel eingestuft. Aus diesem Grund wurde am Institut für Fördertechnik und Logistiksysteme (IFL) ein System entwickelt, welches vorausschauend fahren kann und somit in der Lage ist, in begrenzter Form, auf seine Umgebung zu reagieren.

Implementación de un detector de coral utilizando filtros Gabor Wavelets y máquinas de aprendizaje

Este trabajo se enfoca en la implementación de un detector de arrecife de coral de desempeño rápido que se utiliza para un vehículo autónomo submarino (Autonomous Underwater Vehicle, AUV, por sus siglas en inglés). Una detección rápida de la presencia de coral asegura la estabilización del AUV frente al arrecife en el menor tiempo posible, evitando colisiones con el coral. La detección de coral se hace en una imagen que captura la escena que percibe la cámara del AUV. Se realiza una clasificación píxel por píxel entre dos clases: arrecife de coral y el plano de fondo que no es coral. A cada píxel de la imagen se le asigna un vector característico, el mismo que se genera mediante el uso de filtros Gabor Wavelets. Éstos son implementados en C++ y la librería OpenCV. Los vectores característicos son clasificados a través de nueve algoritmos de máquinas de aprendizaje. El desempeño de cada algoritmo se compara mediante la precisión y el tiempo de ejecución. El algoritmo de Árboles de Decisión resultó ser el más rápido y preciso de entre todos los algoritmos. Se creó una base de datos de 621 imágenes de corales de Belice (110 imágenes de entrenamiento y 511 imágenes de prueba).

Deteção de náufragos com sistemas sonar em UUV’s

Na Marinha Portuguesa, o emprego de Unmanned Underwater Vehicles (UUV) tem uma utilização muito limitada, restringe-se unicamente à deteção de minas. Contudo, com a evolução tecnológica e científica, o seu uso poderá estar a um passo de ser usado em outras vertentes cuja aplicabilidade ainda não foi explorada. Nesta linha de pensamento, surgiu o projeto ICARUS (Integrated Components for Assisted Rescue and Unmanned Search operations), que visa o desenvolvimento de veículos não tripulados para a busca e salvamento. O objetivo do mesmo, resume-se ao salvamento de náufragos com o recurso a UUV, promovendo assim uma eficiente gestão dos recursos, objetivo contemplado na diretiva de planeamento de marinha. Assim, com base no projeto desenvolvido nas teses do ano transato pelos ASPOF Maia da Fonseca e Ramos da Palma, pretende-se com a presente dissertação através de um sistema sonar instalado num UUV em modo upward looking, avaliar a viabilidade na deteção de um náufrago à deriva no mar através das suas leituras. Para tal recorre-se à simulação com o náufrago em diferentes posições e em ambientes mais adequados à realidade que é o mar. E, ainda a otimização das características que permitem a identificação do náufrago.

Environmental modeling with precision navigation using ROAZ autonomous surface vehicle

The use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic systems can relieve human beings of repetitive and dangerous tasks.

Monitoring switch-type sensors and powering autonomous sensors via inductive coupling: application to removable seats in vehicles

Aquesta tesi explora la possibilitat de fer servir enllaços inductius per a una aplicació de l’automòbil on el cablejat entre la centraleta (ECU) i els sensors o detectors és difícil o impossible. S’han proposat dos mètodes: 1) el monitoratge de sensors commutats (dos possibles estats) via acoblament inductiu i 2) la transmissió mitjançant el mateix principi físic de la potència necessària per alimentar els sensors autònoms remots. La detecció d'ocupació i del cinturó de seguretat per a seients desmuntables pot ser implementada amb sistemes sense fils passius basats en circuits ressonants de tipus LC on l'estat dels sensors determina el valor del condensador i, per tant, la freqüència de ressonància. Els canvis en la freqüència són detectats per una bobina situada en el terra del vehicle. S’ha conseguit provar el sistema en un marge entre 0.5 cm i 3 cm. Els experiments s’han dut a terme fent servir un analitzador d’impedàncies connectat a una bobina primària i sensors comercials connectats a un circuit remot. La segona proposta consisteix en transmetre remotament la potència des d’una bobina situada en el terra del vehicle cap a un dispositiu autònom situat en el seient. Aquest dispositiu monitorarà l'estat dels detectors (d'ocupació i de cinturó) i transmetrà les dades mitjançant un transceptor comercial de radiofreqüència o pel mateix enllaç inductiu. S’han avaluat les bobines necessàries per a una freqüència de treball inferior a 150 kHz i s’ha estudiat quin és el regulador de tensió més apropiat per tal d’aconseguir una eficiència global màxima. Quatre tipus de reguladors de tensió s’han analitzat i comparat des del punt de vista de l’eficiència de potència. Els reguladors de tensió de tipus lineal shunt proporcionen una eficiència de potència millor que les altres alternatives, els lineals sèrie i els commutats buck o boost. Les eficiències aconseguides han estat al voltant del 40%, 25% i 10% per les bobines a distàncies 1cm, 1.5cm, i 2cm. Les proves experimentals han mostrat que els sensors autònoms han estat correctament alimentats fins a distàncies de 2.5cm.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes

Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.

Multi-level planning for semi-autonomous vehicles in traffic scenarios based on separation maximization

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem that contributes towards the goal of making road travel by vehicles free of human drivers. An algorithm needs to ensure optimal real time planning of multiple vehicles (moving in either direction along a road), in the presence of a complex obstacle network. Unlike other approaches, here we assume that speed lanes are not present and that different lanes do not need to be maintained for inbound and outbound traffic. Our basic hypothesis is to carry forward the planning task to ensure that a sufficient distance is maintained by each vehicle from all other vehicles, obstacles and road boundaries. We present here a 4-layer planning algorithm that consists of road selection (for selecting the individual roads of traversal to reach the goal), pathway selection (a strategy to avoid and/or overtake obstacles, road diversions and other blockages), pathway distribution (to select the position of a vehicle at every instance of time in a pathway), and trajectory generation (for generating a curve, smooth enough, to allow for the maximum possible speed). Cooperation between vehicles is handled separately at the different levels, the aim being to maximize the separation between vehicles. Simulated results exhibit behaviours of smooth, efficient and safe driving of vehicles in multiple scenarios; along with typical vehicle behaviours including following and overtaking.

Planning autonomous vehicles in the absence of speed lanes using lateral potentials

Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles vary considerably in both their size and speed. Inspired by the performance of artificial potential fields in the planning of mobile robots, we propose here lateral potentials as measures to enable vehicles to decide about their lateral positions on the road. Each vehicle is subjected to a potential from obstacles and vehicles in front, road boundaries, obstacles and vehicles to the side and higher speed vehicles to the rear. All these potentials are lateral and only govern steering the vehicle. A speed control mechanism is also used for longitudinal control of vehicle. The proposed system is shown to perform well for obstacle avoidance, vehicle following and overtaking behaviors.

Planning autonomous vehicles in the absence of speed lanes using an elastic strip

Planning of autonomous vehicles in the absence of speed lanes is a less-researched problem. However, it is an important step toward extending the possibility of autonomous vehicles to countries where speed lanes are not followed. The advantages of having nonlane-oriented traffic include larger traffic bandwidth and more overtaking, which are features that are highlighted when vehicles vary in terms of speed and size. In the most general case, the road would be filled with a complex grid of static obstacles and vehicles of varying speeds. The optimal travel plan consists of a set of maneuvers that enables a vehicle to avoid obstacles and to overtake vehicles in an optimal manner and, in turn, enable other vehicles to overtake. The desired characteristics of this planning scenario include near completeness and near optimality in real time with an unstructured environment, with vehicles essentially displaying a high degree of cooperation and enabling every possible(safe) overtaking procedure to be completed as soon as possible. Challenges addressed in this paper include a (fast) method for initial path generation using an elastic strip, (re-)defining the notion of completeness specific to the problem, and inducing the notion of cooperation in the elastic strip. Using this approach, vehicular behaviors of overtaking, cooperation, vehicle following,obstacle avoidance, etc., are demonstrated.

Heuristic based evolution for the coordination of autonomous vehicles in the absence of speed lanes

The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.