An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Estudi de l’eficiència aerodinàmica de vehicles pesants de transport de passatgers

Estudi de l’eficiència aerodinàmica de les carrosseries de vehicles pesants de cara a reduir el consum de combustible en autocars de llarg trajecte. L’estudi es basa en tres aspectes: validació del programa de simulació, estudi aerodinàmic de diferents carrosseries d’autocar de mercat i estudi aerodinàmic de diferents complements

Influència de l'ús del biodièsel en les emissions contaminants i en el consum de combustible en vehicles pesants

L’objecte d’aquest estudi consisteix en determinar la influència de l’ús del biodièsel en: 1.- Les variacions en comparació amb el combustible convencional (gasoil A) en les emissions de gasos i partícules contaminants en motors de vehicles pesants de transport de mercaderies. 2.- Les variacions en comparació amb el combustible convencional (gasoil A) en el nivell de so emès per motors de vehicles pesants de transport de mercaderies. 3.- Els canvis en el consum de combustible en vehicles pesants en comparació amb la utilització de gasoil A. 4.- Els problemes tècnics observats en motors de vehicles pesants de transport de mercaderies durant un període de funcionament elevat

Estudi de la influència del vent en l’estabilitat de vehicles pesants de transport de viatgers.

Investigacions recents revelen com l’acció del vent lateral és un efecte molt important en bona part dels accidents ocorreguts en vehicles pesants de transport per carretera. És per això que el perfil aerodinàmic del vehicle esdevé determinant en l’avaluació de les forces laterals que hi actuen. El present projecte té per objecte determinar les forces laterals que s’exerceixen en vehicles pesants de transport de passatgers degut a l’acció del vent i investigar-ne la seva perillositat. Per fer-ho s’utilitzen models numèrics de dinàmica de fluids i, per diferents velocitats del vehicle, es simulen vents amb diferent intensitat i direcció. D’aquí es determinen unes condicions de perillositat en funció, entre d’altres variables, de l’angle d’incidència del vent i de la seva velocitat

Aplicació de la tècnica d’ espectroscòpia d’ absorció atòmica de flama com a eina per al manteniment de vehicles

L’objectiu d’aquest projecte fi de carrera és en primer lloc, determinar les modificacions a realitzar en el laboratori de lubricants i combustibles de l’EPS per a la utilització de l’espectrofotòmetre d’absorció atòmica de flama; en segon lloc, posar a punt l’aparell establint els paràmetres i les condicions d’assaig idònies per a portar a terme les anàlisis de metalls de desgast presents en olis lubricants usats de motors de combustió interna. I finalment, establir un protocol de treball al laboratori i estudiar la viabilitat d’oferir el servei d’anàlisi de lubricants a empreses i particulars

Projecte d’instal∙lacions d’un edifici mixte d’habitatges, local industrial i aparcament

Aquest projecte tracta d’un estudi tècnic, disseny i càlcul de les instal∙lacions d’un edifici mixte d’habitatges, local comercial i zona d’aparcament, complint la normativa que li pertoca segons l’ús a que es destina l’espai. L’edifici objecte d’aquest projecte es troba situat a la cruïlla Platja d’Aro s/n de la localitat de Santa Cristina d’Aro, i es tracta com un edifici de nova construcció. L’abast del projecte contempla les instal∙lacions elèctriques, tèrmiques, contra incendis, sanejament i de salubritat, per tal d’assolir les fases executives del projecte, així com les legalitzacions de les diferents activitats que es desenvolupen a l’edifici (aparcament de vehicles, comercial, taller de reparació de vehicles a motor i d’ús administratiu). Es pretén fer un estudi integral de les instal∙lacions i mesures correctores que es poden realitzar en un edifici amb les característiques esmentades

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

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

Using petri nets to specify and execute missions for autonomous underwater vehicles

This paper presents the design and implementation of a mission control system (MCS) for an autonomous underwater vehicle (AUV) based on Petri nets. In the proposed approach the Petri nets are used to specify as well as to execute the desired autonomous vehicle mission. The mission is easily described using an imperative programming language called mission control language (MCL) that formally describes the mission execution thread. A mission control language compiler (MCL-C) able to automatically translate the MCL into a Petri net is described and a real-time Petri net player that allows to execute the resulting Petri net onboard an AUV are also presented

ICTINEUAUV wins the First SAUC-E competition

A pioneer team of students of the University of Girona decided to design and develop an autonomous underwater vehicle (AUV) called ICTINEU-AUV to face the Student Autonomous Underwater Challenge-Europe (SAUC-E). The prototype has evolved from the initial computer aided design (CAD) model to become an operative AUV in the short period of seven months. The open frame and modular design principles together with the compatibility with other robots previously developed at the lab have provided the main design philosophy. Hence, at the robot's core, two networked computers give access to a wide set of sensors and actuators. The Gentoo/Linux distribution was chosen as the onboard operating system. A software architecture based on a set of distributed objects with soft real time capabilities was developed and a hybrid control architecture including mission control, a behavioural layer and a robust map-based localization algorithm made ICTINEU-AUV the winning entry

On AUV control architecture

This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed