Contribució al posicionament dinàmic de robots mòbils per mitjà d'un sistema làser

Aquesta tesi tracta el problema del posicionament de robots mòbils quan, en el decurs del moviment, es realitzen mesures angulars relatives al robot de l'orientació de la recta entre un dels seus punts i punts de l'entorn de posició coneguda. Es considera que les mesures angulars són fetes per un sensor làser giratori que detecta diferents reflectors catadiòptrics fixos. La contribució principal és el desenvolupament d'un algorisme dinàmic, basat en un filtre de Kalman estès (EKF), que estima a cada instant de temps l'estat format pels angles associats als reflectors. La simulació hodomètrica dels angles entre mesures directes del sensor làser garanteix l'ús consistent i continuat dels mètodes de triangulació per a determinar la posició i l'orientació del robot. Inclou simulacions informàtiques i experiments per a validar la precisió del mètode de posicionament proposat. En l'experimentació s'utilitza un robot mòbil omnidireccional amb tres rodes de lliscament direccional de corrons esfèrics.

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Control remoto (web) de un robot Aibo

El robot Aibo disposa de la llibreria Aibo Remote Framework per controlar-lo remotament mitjançant un PC i una xarxa inalàmbrica, també per accedir a informació d'estat del robot, o per veure les imatges que l'Aibo capta. Combinant Remote Framework i php s'ha creat una aplicació web que permet controlar Aibos diferents remotament per Internet, així com tenir accés a les imatges subjectives de cadascun dels Aibos. A més, la tecnologia existent d'streaming permet que l'aplicació web tingui un vídeo incrustat que possibilita veure en directe els Aibos mitjançant una càmera web enfocada cap a ells.

Anàlisi, disseny i construcció d'un robot educatiu basat en microcontrolador AVR-ATMEGA

Aquest projecte presenta el disseny, construcció i programació d’un robot autònom, com a base per una proposta educativa. Per aconseguir aquest objectiu s’ha dotat el robot d’una unitat de procés, un sistema de locomoció i un seguit de sensors que proporcionaran a la unitat informació respecte l’entorn. Per gestionar totes aquestes funcionalitats, s’ha fet servir un sistema operatiu en temps real capaç de gestionar amb efectivitat les tasques que puguin ser executades pel robot. Finalment, s’ha exposat una detallada descripció dels costos per una producció de volum mig i de caire merament educatiu.

Estudi: microcontrolador LPC2119 - ARM. Cas pràctic: anàlisi, disseny i construcció d'un robot amb pèndul invertit

Estudi de l'arquitectura i prestacions del microcontrolador LPC2119 tot implementant la proposta d’un cas pràctic. En la besant teòrica, es fa una anàlisi acurada del dispositiu LPC2119, enumerant les principals característiques i exposant les seves parts, aprofundint sobretot en l’arquitectura i core ARM que incorpora. En l'àmbit pràctic, s'introdueix el problema del pèndul invertit com a proposta per a ser integrada sobre un robot que exploti les funcionalitats del dispositiu integrat presentades a l'estudi teòric.

Utilització del robot mòbil com a eina d'aprenentatge en ensenyaments tècnics

En aquest Projecte de Millora de la Qualitat Docent es descriu el disseny, la construcció i la utilització d’un robot mòbil com a eina docent en titulacions d’Enginyeria. El robot mòbil té com a element de control un PC portàtil convencional per tal de facilitar el procés d’aprenentatge de l’alumnat estigui centrat en l’objectiu de les pràctiques i no en el funcionament i control del robot. A més a més, el robot disposa d’un elevat nombre de sensors i actuadors per tal d’oferir un elevat grau d’interdisciplinaritat.

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

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

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

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

An approach to vision-based station keeping for an unmanned underwater vehicle

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

A system to evaluate the accuracy of a visual mosaicking methodology

When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system