CRIIS - Other Publications

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Browsing CRIIS - Other Publications by Author "António Paulo Moreira"
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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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    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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    Evaluation of sensors and algorithms for person detection for personal robots
    ( 2013) Tonelo,C ; António Paulo Moreira ; Germano Veiga
    The main objective of this project was to evaluate the sensing system for person detection in the scope of its integration in a mobile robotic platform for Ambient Assisted Living. Two sensors were considered, a camera and a depth sensor. For the camera (2D), 3 different algorithms were implemented: face detection, tracking and recognition. For the depth sensor the whole body detection was tested using skeleton tracking. The results showed that the face detection and recognition algorithms had a very small range, and the face tracking demonstrated to reach a higher distance. However, the latter exhibited poor results when confronted with illumination variations. The skeleton tracking algorithm provided good results, being capable of tracking relatively close to the sensor and up to 3 meters distance. Thus, the 2D face recognition can be used for short distances to identify the person, while the 3D skeleton tracking can be appropriated for distant tracking of the person. This work showed that the integration of these sensing systems, in a robotic platform, can make a robust robot capable of human interaction in home environments. © 2013 IEEE.
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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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    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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    Humanoid Gait Optimization Resorting to an Improved Simulation Model
    ( 2013) José Lima ; José Alexandre Gonçalves ; Paulo José Costa ; António Paulo Moreira
    The simulation of a robot with a high number of joints can easily become unstable. Numerical errors on the first joint of the chain are propagated to the other joints. This is a very common problem in humanoid robots. A way to plan the gait for these robots is using simulation and optimization techniques. This paper addresses a new approach to optimizing gait parameter sets using an adaptive simulated annealing optimization algorithm, combined with a new joint model that reduces its instability. The new model and the optimization are implemented in SimTwo (a developed physical robot simulator that is capable of simulating user defined robots in a three-dimensional space, since it includes a physical model based on rigid body dynamics) and results are shown that validate the approach.
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    Increasing Illumination Invariance of SURF Feature Detector through Color Constancy
    ( 2013) Petry,MR ; António Paulo Moreira ; Luís Paulo Reis
    Most of the original image feature detectors are not able to cope with large photometric variations, and their extensions that should improve detection eventually increase the computational cost and introduce more noise to the system. Here we extend the original SURF algorithm increasing its invariance to illumination changes. Our approach uses the local space average color descriptor as working space to detect invariant features. A theoretical analysis demonstrates the impact of distinct photometric variations on the response of blob-like features detected with the SURF algorithm. Experimental results demonstrate the effectiveness of the approach in several illumination conditions including the presence of two or more distinct light sources, variations in color, in offset and scale.
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    Intelligent state changing applied to multi-robot systems
    ( 2013) Nascimento,TP ; António Paulo Moreira ; Scolari Conceicao,AGS ; Bonarini,A
    The target searching problem is a situation where a formation of multi-robot systems is set to search for a target and converge towards it when it is found. This problem lies in the fact that the target is initially absent and the formation must search for it in the environment. During the target search, false targets may appear dragging the formation towards it. Therefore, in order to avoid the formation following a false target, this paper presents a new methodology using the Takagi-Sugeno type fuzzy automaton (TS-TFA) in the area of formation control to solve the target searching problem. The TS fuzzy system is used to change the formation through the modifications in the states of the automaton. This change does not only switch the rules and therefore the state of each robot, but also the controllers and cost functions. This approach amplifies the versatility of the formation of mobile robots in the target searching problem. In this paper, the TS-TFA is presented and its implications in the formation are explained. Simulations and results with real robot are presented where it can be noticed that the formation is broken to maximize the perception range based on each robot's observation of a possible target. Finally this work is concluded in the last section.
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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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    Lecture Notes in Electrical Engineering: Preface
    ( 2015) António Paulo Moreira ; Aníbal Matos ; Germano Veiga
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    Modeling and simulation of a laser scanner sensor: An industrial application case study
    ( 2013) José Lima ; José Alexandre Gonçalves ; Paulo José Costa ; António Paulo Moreira
    A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. At the same time, simulation has becoming more and more used in industries and academia since it presents several advantages. It takes the building and rebuilding phase out of the loop by using the model already created in the design phase. Further, simulation time on testing is cheaper and faster than performing the multiple tests of the design each time. Besides, it is easier to measure some variables in simulation than in real scenarios. In this paper, a laser scanner sensor is modeled and implemented in a developed simulator that already has several other sensors and actuators models. The presented simulation reflects the laser model properties such as target color dependences, noise, limits, time constraints, and target angle functions. As a case study, the same scenario is assembled with real components on a conveyer belt and in simulation. Results from both approaches are compared and validate the proposed model methodology. As an example, a 3D object recognition task is addressed highlighting the developed realistic model. Further industrial and R&D implementations based on this sensor could be stressed in simulation before implementation. © Springer International Publishing Switzerland 2013.
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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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    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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    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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    Perception-Driven Multi-Robot Formation Control
    ( 2013) Ahmad,A ; Nascimento,T ; Conceicao,AGS ; António Paulo Moreira ; Lima,P
    Maximizing the performance of cooperative perception of a tracked target by a team of mobile robots while maintaining the team's formation is the core problem addressed in this work. We propose a solution by integrating the controller and the estimator modules in a formation control loop. The controller module is a distributed non-linear model predictive controller and the estimator module is based on a particle filter for cooperative target tracking. A formal description of the integration followed by simulation and real robot results on two different teams of homogeneous robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target's cooperative estimate while complying with the performance criteria such as keeping a pre-set distance between the team-mates and/or the target and obstacle avoidance.
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    Preface
    ( 2017) Garrido,P ; Soares,F ; António Paulo Moreira
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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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    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.
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    Real-time tracking system for a moored oil tanker: A Kalman filter approach
    ( 2013) Malheiros,P ; Rosa Santos,P ; José Alexandre Gonçalves ; Paulo José Costa ; António Paulo Moreira ; Veloso Gomes,F ; Taveira Pinto,F
    This paper presents a tracking system developed to study the behavior of an oil tanker moored at the Berth ‘‘A’’ of the Leixões Oil Terminal, Porto, Portugal. A brief description of the local environmental conditions and the existing operational conditions at that oil terminal are presented. Due to extreme outdoor working conditions a Kalman filter was implemented to ensure the robustness and reliability of the obtained measurements. Tests were performed in laboratory on a physical model of a moored oil tanker at a scale 1/100. The results were compared with a commercial motion capture system installed in laboratory. The presented measurement system was developed as part of the DOLPHIN project that aims to study the behavior of moored ships in harbors. © Springer International Publishing Switzerland 2013.
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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.