CRIIS - Other Publications

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    Anechoic Chamber Interference Tests on a Bluetooth Low Energy Front-End Towards a Subcutaneous Glucose Sensor
    ( 2012) Sérgio Santos Silva ; António Paulo Moreira ; Salviano Soares ; António Valente
    Background: The metabolic disorder which entails the absent or reduced control of blood glucose in the body by means of insulin dependence (Type 1) or intolerance (Type 2) affected more than 382 million people in 2013. Although only 13% of patients die from diabetes, there are a significant number of costly, dangerous health complications that appear if the correct control is not taken. Glucose subcutaneous Bluetooth Low-Energy sensor can help patients to constantly monitor their glucose levels and issue alarms to a cellular phone. Several tests regarding interference, robustness and coexistence were made to ensure Quality of Service in order to achieve medical diagnostic status. Materials and Methods: All measurements were performed in a full anechoic chamber with walls, ceiling and floor covered with high loss microwave absorbers. A PC USB Dongle acts as receiver for the Java developed application, where several data sets for each location were recorded.
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    Modeling and simulation of the EMG30 geared motor with encoder resorting to simtwo: The official robot@factory simulator
    ( 2013) José Alexandre Gonçalves ; José Lima ; Paulo José Costa ; António Paulo Moreira
    This paper describes the EMG30 mechanical and electrical modeling and its simulation resorting to SimTwo (Robot@Factory mobile robot competition official simulator). It is described the developed setup applied to obtain the experimental data that was used to estimate the actuator parameters. It was obtained an electro-mechanical dynamical model that describes the motor, its gear box, and the encoder. The motivation to model and simulate the EMG30 is the fact that it is an actuator worldwide popular in the mobile robotics domain, being a low cost 12v motor equipped with encoders and a 30:1 reduction gearbox. The Goal of this work is to provide more realism and new features to the Robot@Factory official simulator, allowing participating teams to produce and validate different robot prototypes and its software, reducing considerably the development time. © Springer International Publishing Switzerland 2013.
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    Ocean Observation With Coordinated Robotic Platforms Coordination Algorithms Maintain Vehicle Formation
    ( 2013) Nuno Cruz ; Bruno Miguel Ferreira ; Aníbal Matos
    The MARES is a small, torpedo-shaped AUV 1.5 meters long and 32 kilograms in weight in the basic version. In a typical configuration, a PC/104 computational system manages the entire mission, including communications with other devices and a control station. Navigation is provided by the fusion of data from an inertial measurement unit (IMU) and an acoustic system for long baseline localization (LBL), complemented by a small GPS receiver, when the vehicle is at the surface. Four thrusters provide the capability to move as fast as 5 knots and to hover in the water column, with a set of lithium-ion batteries ensuring 10 hours of operation. MARES is a highly modular vehicle, with the ability to integrate a great variety of payload sensors, and it has been operating since 2007, mainly in environmental- monitoring missions. The capability of vehicles to follow a given trajectory and maintain reliable data exchange is among the most relevant topics when it comes to coordination of marine robots.
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    Object recognition using laser range finder and machine learning techniques
    ( 2013) Andry Maykol Pinto ; Luís Freitas Rocha ; António Paulo Moreira
    In recent years, computer vision has been widely used on industrial environments, allowing robots to perform important tasks like quality control, inspection and recognition. Vision systems are typically used to determine the position and orientation of objects in the workstation, enabling them to be transported and assembled by a robotic cell (e.g. industrial manipulator). These systems commonly resort to CCD (Charge-Coupled Device) Cameras fixed and located in a particular work area or attached directly to the robotic arm (eye-in-hand vision system). Although it is a valid approach, the performance of these vision systems is directly influenced by the industrial environment lighting. Taking all these into consideration, a new approach is proposed for eye-on-hand systems, where the use of cameras will be replaced by the 2D Laser Range Finder (LRF). The LRF will be attached to a robotic manipulator, which executes a pre-defined path to produce grayscale images of the workstation. With this technique the environment lighting interference is minimized resulting in a more reliable and robust computer vision system. After the grayscale image is created, this work focuses on the recognition and classification of different objects using inherent features (based on the invariant moments of Hu) with the most well-known machine learning models: k-Nearest Neighbor (kNN), Neural Networks (NNs) and Support Vector Machines (SVMs). In order to achieve a good performance for each classification model, a wrapper method is used to select one good subset of features, as well as an assessment model technique called K-fold cross-validation to adjust the parameters of the classifiers. The performance of the models is also compared, achieving performances of 83.5% for kNN, 95.5% for the NN and 98.9% for the SVM (generalized accuracy). These high performances are related with the feature selection algorithm based on the simulated annealing heuristic, and the model assessment (k-fold cross-validation). It makes possible to identify the most important features in the recognition process, as well as the adjustment of the best parameters for the machine learning models, increasing the classification ratio of the work objects present in the robot's environment.
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    Robot@Factory: Localization Method Based on Map-Matching and Particle Swarm Optimization
    ( 2013) Andry Maykol Pinto ; António Paulo Moreira ; Paulo José Costa
    This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the Robot@Factory which is a new robotic competition presented in Lisbon 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that is well-behaved. The sensor information is continuously updated in time and space through the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, a particle filter based on Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high. Meaning that the map-matching is unreliable and robot is lost. The experiments conducted in this paper prove the ability and accuracy of the presented technique to localize small mobile robots for this competition. Therefore, extensive results show that the proposed method have an interesting localization capability for robots equipped with a limited amount of sensors.
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    FEUPCAR 2.0: Overview of a Low-cost Robot for Autonomous Driving Competitions
    ( 2013) Vidal,AA ; Luís Paulo Reis ; António Paulo Moreira
    Robotic autonomous driving is a very complex task that tries to replicate the human behavior when performing such task. This paper presents a high-level overview of an architecture applicable for small-scale vehicles in autonomous driving competitions. A special emphasis is given on the sensory and navigation sub-systems since they are the most prominent intelligent decision layers. The former is almost entirely based on computer vision, processing the raw image content from two ordinary and inexpensive "web-cams", conveying further relevant information to the later, on a real-time basis. The proposed architecture was implemented with minimal interventions to an Ackermann-like vehicle which was originally designed for recreational purposes, serving as a "proof of concept" of the developed system. Results show that a low-cost, scalable and modular system can be easily integrated on regular small-scale vehicles obtaining exciting results at a minimal cost.
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    Semi-automatic Virtual Reconstruction of Ancient Roman Houses
    ( 2013) Telmo Oliveira Adão ; Luís Gonzaga Magalhães ; Emanuel Peres Correia
    Video Games may be used with different applications in mind, for entertainment, training and simulation or even as teaching tools. However, the production of contents for such games, namely game scenarios with virtual worlds composed by cities and related elements (streets, buildings, furniture and so on) may require a laborious effort by multidisciplinary teams which lead to an expensive and time consuming solution. In order to avoid the development burden, procedural modeling techniques have been created and applied to generate virtual models of buildings and cities expeditiously with high degree of detail and realism. Nevertheless, most of the existing techniques use complex sets of rules to produce models without being aware of the architectonic structures and its relationships. Thereby, in order to simplify the generation process and rule dealing we propose, in this paper, an ontology-based procedural modeling methodology which integrates an ontological structure, describing city elements and the relationships between each other, and a combined set of procedural techniques to generate roman houses. The preliminary results point to a method capable of producing roman houses expeditiously, including the interiors and the exteriors.
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    Multi-robot nonlinear model predictive formation control: Moving target and target absence
    ( 2013) Nascimento,TP ; António Paulo Moreira ; Scolari Conceicao,AGS
    This paper describes a novel approach in formation control for mobile robots in the active target tracking problem. A nonlinear model predictive formation controller (NMPFC) for target perception was implemented to converge a group of mobile robots toward a desired target. The team must also maintain a desired formation following a target while it is moving, or follow a leader in the case of target's absence. The structure details of the controller, as well as a mathematical analysis of the formation model used, are presented. Furthermore, results of simulations and experiments with real robots are presented and discussed.
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    Entropy Diversity in Multi-Objective Particle Swarm Optimization
    ( 2013) Eduardo Pires ; Tenreiro Machado,JAT ; Paulo Moura Oliveira
    Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyze the MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.
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    IntellWheels: Intelligent wheelchair with user-centered design
    ( 2013) Petry,MR ; António Paulo Moreira ; Brígida Mónica Faria ; Luís Paulo Reis
    Intelligent wheelchairs can become an important solution to assist physically impaired individuals who find it difficult or impossible to drive regular powered wheelchairs. However, when designing the hardware architecture several projects compromise the user comfort and the wheelchair normal usability in order to solve robotic problems. In this paper we describe the main concepts regarding the design of the IntellWheels intelligent wheelchair. Our approach has a user-centered perspective, in which the needs and limitations of physically impaired users are given extensive attention at each stage of the design process. Finally, our design was evaluated through a public opinion assessment. A statistical analysis suggested that the design was effective to mitigate the visual and ergonomic impacts caused by the addition of sensorial and processing capabilities on the wheelchair. © 2013 IEEE.
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    Self-localisation of indoor mobile robots using multi-hypotheses and a matching algorithm
    ( 2013) Pinto,M ; Héber Miguel Sobreira ; António Paulo Moreira ; Hélio Mendonça ; Aníbal Matos
    This paper proposes a new, fast and computationally light weight methodology to pinpoint a robot in a structured scenario. The localisation algorithm performs a tracking routine to pinpoint the robot's pose as it moves in a known map, without the need for preparing the environment, with artificial landmarks or beacons. To perform such tracking routine, it is necessary to know the initial position of the vehicle. This paper describes the tracking routine and presents a solution to pinpoint that initial position in an autonomous way, using a multi-hypotheses strategy. This paper presents experimental results on the performance of the proposed method applied in two different scenarios: (1) in the Middle Size Soccer Robotic League (MSL), using artificial vision data from an omnidirectional robot and (2) in indoor environments using 3D data from a tilting Laser Range Finder of a differential drive robot (called RobVigil). This paper presents results comparing the proposed methodology and an Industrial Positioning System (the Sick NAV350), commonly used to locate Autonomous Guided Vehicles (AGVs) with a high degree of accuracy in industrial environments.
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    Recognizing Industrial Manipulated Parts Using the Perfect Match Algorithm
    ( 2013) Luís Freitas Rocha ; Ferreira,M ; Germano Veiga ; António Paulo Moreira ; Santos,V
    The objective of this work is to develop a highly robust 3D part localization and recognition algorithm. This research work is driven by the needs specified by enterprises with small production series that seek for full robotic automation in their production line, which processes a wide range of products and cannot use dedicated identification devices due to technological processes. With the correct classification of the part, the robot will be able to autonomously select the correct program to execute. For this purpose, the Perfect Match algorithm, which is known by its computational efficiency, high precision and robustness, was adapted for object recognition achieving a 99.7% of classification rate. The expected practical implication of this work is contributing to the integration of industrial robots in highly dynamic and specialized lines, reducing the companies' dependency on skilled operators.
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    State operation optimization in electrical networks
    ( 2013) Pereira,P ; Leitao,S ; Eduardo Pires
    This paper makes a study about optimal supply of the energy service, using simulations of network operation scenarios, in order to optimize resources and minimize the variables: operation cost, energy losses, generation cost and consumers shedding. These simulations create optimal operation models of the network, allowing the system operator obtain knowledge to take pre-established procedures that must be performed in situations of contingency in order to forecast and minimize drawbacks. The simulations were performed using a multiobjective particle swarm optimization algorithm. The algorithm was applied to the IEEE 14 Bus network where the optimal power flow was evaluated by MATPOWER tool to establish an optimal electrical working model to minimize the associated costs. © 2013 IEEE.
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    Towards Extraction of Topological Maps from 2D and 3D Occupancy Grids
    ( 2013) Filipe Neves Santos ; António Paulo Moreira ; Paulo José Costa
    Cooperation with humans is a requirement for the next generation of robots so it is necessary to model how robots can sense, know, share and acquire knowledge from human interaction. Instead of traditional SLAM (Simultaneous Localization and Mapping) methods, which do not interpret sensor information other than at the geometric level, these capabilities require an environment map representation similar to the human representation. Topological maps are one option to translate these geometric maps into a more abstract representation of the the world and to make the robot knowledge closer to the human perception. In this paper is presented a novel approach to translate 3D grid map into a topological map. This approach was optimized to obtain similar results to those obtained when the task is performed by a human. Also, a novel feature of this approach is the augmentation of topological map with features such as walls and doors.
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    Radiation tests on a bluetooth based front-end electronic device towards a subcutaneous continuous glucose monitoring sensor
    ( 2013) Sérgio Santos Silva ; Soares,S ; António Valente ; António Paulo Moreira
    The metabolic disorder which entails the absent or reduced control of blood glucose in the body by means of insulin dependence (Type 1) or intolerance (Type 2) affected more than 366 million people in 2011. This represents an increase of 28% new cases in one year. Diabetes Mellitus has become the most common chronic diseases in nearly all countries, and continues to increase in numbers and significance, as economic development and urbanization lead to changing lifestyles characterized by reduced physical activity, and increased obesity. Recent advances in wireless sensor networking technology have led to the development of low cost, low power, multifunctional sensor nodes that enable environment sensing together with data processing. Instrumented with a variety of sensors, such as temperature, humidity, volatile compound detection, bio implanted sensors; the development of such networks requires testing for transmission distance and human body interference. As Bluetooth Low-Energy (BLE) operates in the free 2.4GHz ISM band, the same band that Wi-Fi signals operate, tests regarding interference, robustness and coexistence must be made in order to ensure Quality of Service (QoS) and therefore achieve medical diagnostic equipment status. This paper presents a BLE prototype and compares the results obtained in terms of radiated power over distance with and without physical barriers. © 2013 The Science and Information Organization.
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    Fast 3D Map Matching Localisation Algorithm
    ( 2013) Pinto,M ; António Paulo Moreira ; Aníbal Matos ; Héber Miguel Sobreira ; Filipe Neves Santos
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    Support System for Rational Use of Electric Energy
    ( 2013) Teixeira,T ; Benedita Malheiro
    This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform -the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.
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    3-D Position Estimation from Inertial Sensing: Minimizing the Error from the Process of Double Integration of Accelerations
    ( 2013) Neto,P ; Norberto Pires,JN ; António Paulo Moreira
    This paper introduces a new approach to 3-D position estimation from acceleration data, i.e., a 3-D motion tracking system having a small size and low-cost magnetic and inertial measurement unit (MIMU) composed by both a digital compass and a gyroscope as interaction technology. A major challenge is to minimize the error caused by the process of double integration of accelerations due to motion (these ones have to be separated from the accelerations due to gravity). Owing to drift error, position estimation cannot be performed with adequate accuracy for periods longer than few seconds. For this reason, we propose a method to detect motion stops and only integrate accelerations in moments of effective hand motion during the demonstration process. The proposed system is validated and evaluated with experiments reporting a common daily life pick-and-place task.
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    Investigation of Underwater Acoustic Networking Enabling the Cooperative Operation of Multiple Heterogeneous Vehicles
    ( 2013) Nuno Cruz ; Bruno Miguel Ferreira ; Kebkal,O ; Aníbal Matos ; Petrioli,C ; Petroccia,R ; Spaccini,D
    In this paper, we investigate the creation of an underwater acoustic network to support marine operations based on static and mobile nodes. Each underwater device combines communication, networking, and sensing capabilities and cooperates with the other devices in coordinated missions. The proposed system is built upon the SUNSET framework, providing acoustic communications and networking capabilities to autonomous underwater vehicles, autonomous surface vessels, and moored systems, using underwater acoustic modems. Specific solutions have been developed and tested to control the underwater nodes acoustically and to instruct the vehicles on keeping a given formation using acoustic links. One of the novelties of our approach has been the development and utilization of a realistic simulation infrastructure to provide a very accurate representation of all the dynamic systems involved in the network, modeling the vehicle dynamics, the acoustic channel, and the communication messages. This infrastructure has been extensively used to investigate and validate the proposed solutions under different environmental conditions before the actual deployment of devices. Several experiments were then conducted in the laboratory and in the field. The experimental results have confirmed the effectiveness of the proposed solutions and the reliability of the proposed simulation framework in estimating system performance.
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    Real-Time and Continuous Hand Gesture Spotting: an Approach Based on Artificial Neural Networks
    ( 2013) Neto,P ; Pereira,D ; Norberto Pires,JN ; António Paulo Moreira
    New and more natural human-robot interfaces are of crucial interest to the evolution of robotics. This paper addresses continuous and real-time hand gesture spotting, i.e., gesture segmentation plus gesture recognition. Gesture patterns are recognized by using artificial neural networks (ANNs) specifically adapted to the process of controlling an industrial robot. Since in continuous gesture recognition the communicative gestures appear intermittently with the non-communicative, we are proposing a new architecture with two ANNs in series to recognize both kinds of gesture. A data glove is used as interface technology. Experimental results demonstrated that the proposed solution presents high recognition rates (over 99% for a library of ten gestures and over 96% for a library of thirty gestures), low training and learning time and a good capacity to generalize from particular situations.