CRIIS - Book Chapters

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    3 DoF/6 DoF Localization System for Low Computing Power Mobile Robot Platforms
    ( 2015) Carlos Miguel Costa ; Héber Miguel Sobreira ; Armando Sousa ; Germano Veiga
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    Classification of an Agrosilvopastoral System Using RGB Imagery from an Unmanned Aerial Vehicle
    ( 2019) Guimarães,N ; Emanuel Peres Correia ; Marques,P ; Telmo Oliveira Adão ; Pádua,L ; Sousa,JJ ; Sousa,A ; 5653 ; 5490
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    Conflict Resolution Problem Solving with Bio-Inspired Metaheuristics:
    ( 2016) Paulo Moura Oliveira ; Eduardo Pires
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    Development of an AGV controlled by fuzzy logic
    ( 2013) Barbosa,RS ; Manuel Santos Silva ; Osório,DJ ; 5655
    This paper presents the development of a behavior-based AGV using fuzzy logic. A robot platform and a fuzzy logic controller (FLC) are developed for the embodiment of different behaviors. Experimental results are given to assess the performance of the AGV and to validate the proposed design schemes for its construction and control. © 2013, Springer Science Business Media Dordrecht.
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    Dynamic Collision Avoidance System for a Manipulator Based on RGB-D Data
    ( 2017) Brito,T ; Lima,J ; Pedro Gomes Costa ; Piardi,L
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    Fault Tolerant Depth Control of the MARES AUV
    ( 2011) Bruno Miguel Ferreira ; Aníbal Matos ; Nuno Cruz
    Control theory has been applied to several domains where practical considerations are relevant. Robotics is a notable example of this. In most cases, mobile robotic systems are governed such that their behavior obeys to a defined motion. However, during their operations, it is conceivable that faults could occur. Indeed, this assumption has to be made in order to predict a possible malfunction and to take an appropriate action according to the fault, improving the robustness and the reliability of the system. This work tackles the problem of fault detection, identification and automatic reconfiguration of an autonomous underwater vehicle (AUV). Although our emphasis will be directed to an AUV, the methods and the tools that are employed in this chapter can be easily extended to other engineering problems beyond robotics.
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    Flexible work cell simulator using digital twin methodology for highly complex systems in industry 4.0
    ( 2018) Tavares,P ; Silva,JA ; Pedro Gomes Costa ; Veiga,G ; Moreira,AP
    The continuous evolution in manufacturing processes has attracted substantial interest from both scientific and research community, as well as from industry. Despite the fact that streamline manufacturing relies on automation systems, most production lines within the industrial environment lack a flexible framework that allows for evaluation and optimisation of the manufacturing process. Consequently, the development of a generic simulators able to mimic any given workflow represent a promising approach within the manufacturing industry. Recently the concept of digital twin methodology has been introduced to mimic the real world through a virtual substitute, such as, a simulator. In this paper, a solution capable of representing any industrial work cell and its properties is presented. Here we describe the key stages of such solution which has enough flexibility to be applied to different working scenarios commonly found in industrial environment. © 2018, Springer International Publishing AG.
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    Fractional particle swarm optimization
    ( 2014) Eduardo Pires ; Machado,JAT ; Paulo Moura Oliveira
    The paper addresses new perspective of the PSO including a fractional block. The local gain is replaced by one of fractional order considering several previous positions of the PSO particles. The algorithm is evaluated for several well known test functions and the relationship between the fractional order and the convergence of the algorithm is observed. The fractional order influences directly the algorithm convergencerate demonstrating a large potential for developments. © Springer Science+Business Media Dordrecht 2014.
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    The K-framed quadtrees approach for path planning through a known environment
    ( 2018) Ana Rita Rodrigues ; Pedro Gomes Costa ; Lima,J
    One of the most important tasks for a mobile robot is to navigate in an environment. The path planning is required to design the trajectory that generates useful motions from the original to the desired position. There are several methodologies to perform the path planning. In this paper, a new method of approximate cells decomposition, called K-Framed Quadtrees is present, to which the algorithm A ? is applied to determine trajectories between two points. To validate the new approach, we made a comparative analysis between the present method, the grid decomposition, quadtree decomposition and framed quadtree decomposition. Results and implementation specifications of the four methods are presented. © 2018, Springer International Publishing AG.
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    Magnetic wheeled climbing robot: Design and implementation
    ( 2013) Manuel Santos Silva ; Barbosa,RS ; Oliveira,ALC ; 5655
    This paper presents a climbing robot, with wheeled locomotion and adhesion through permanent magnets. This machine was developed to be used in the inspection of several types of man-made ferromagnetic structures, such as towers for wind turbines, fuel storage tanks, ship hulls, etc., in order to, for instance, detect weaknesses due to corrosion. In this article are presented the main aspects taken into consideration for its design, as well as several constructive aspects, among which are detailed its mechanical and electrical construction, the implemented control architecture and the Human-Machine Interface (HMI) for its control. The distinguishing characteristic of this robot is its dynamic adjustment system of the permanent magnets to assure the machine adhesion to the surfaces when crossing slightly irregular and curved surfaces with a large radius. © 2013, Springer Science Business Media Dordrecht.
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    MEMS Devices in Agriculture
    ( 2016) António Valente
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    Meta-heuristics Self-Parameterization in a Multi-Agent Scheduling System Using Case-Based Reasoning
    ( 2012) Paulo Moura Oliveira ; Ivo Pereira ; Ana Madureira
    This paper proposes a novel agent-based approach to Meta-Heuristics self-configuration. Meta-heuristics are algorithms with parameters which need to be set up as efficient as possible in order to unsure its performance. A learning module for self-parameterization of Meta-heuristics (MH) in a Multi-Agent System (MAS) for resolution of scheduling problems is proposed in this work. The learning module is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. Finally, some conclusions are reached and future work outlined
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    Offline Programming of Collision Free Trajectories for Palletizing Robots
    ( 2017) Silva,R ; Luís Freitas Rocha ; Relvas,P ; Pedro Gomes Costa ; Manuel Santos Silva
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    Optimization of quadruped robot locomotion gaits through a genetic algorithm
    ( 2014) Manuel Santos Silva
    During the last years research and development on legged robots has grown steadily. Leggedsystems present major advantages when compared with “traditional” vehicles, allowinglocomotion in terrain inaccessible to vehicles with wheels and tracks. However, its energy consumption still lag being these vehicles, existing several aspects that need to be improvedand optimized.One of them regards the parameters values that these machines should adopt to minimize the energy consumption. Due to the large number of parameters involved in this optimization process one way to achieve meaningful results is using evolutionary strategies. Genetic Algorithms are away to “imitate nature”replicating the process that nature designed forthe generation and evolutionof species. The objective of this paper is to present a genetic algorithm, running over a simulationapplication oflegged robots, which allows the optimization of several parameters of a quadrupedrobot model, for distinct locomotion gaits. © Springer Science+Business Media Dordrecht 2014.
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    Path planning for automatic recharging system for steep-slope vineyard robots
    ( 2018) Luís Carlos Santos ; Filipe Neves Santos ; Mendes,J ; Ferraz,N ; Lima,J ; Morais,R ; Costa,P
    Develop cost-effective ground robots for crop monitoring in steep slope vineyards is a complex challenge. The terrain presents harsh conditions for mobile robots and most of the time there is no one available to give support to the robots. So, a fully autonomous steep-slope robot requires a robust automatic recharging system. This work proposes a multilevel system that monitors a vineyard robot autonomy, to plan off-line the trajectory to the nearest recharging point and dock the robot on that recharging point considering visual tags. The proposed system called VineRecharge was developed to be deployed into a cost-effective robot with low computational power. Besides, this paper benchmarks several visual tags and detectors and integrates the best one into the VineRecharge system. © Springer International Publishing AG 2018.
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    Pose Invariant Object Recognition Using a Bag of Words Approach
    ( 2017) Carlos Miguel Costa ; Armando Sousa ; Germano Veiga
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    Poses Optimisation Methodology for High Redundancy Robotic Systems
    ( 2017) Tavares,P ; Pedro Gomes Costa ; Veiga,G ; Moreira,AP
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    Reconstructing the Past
    ( 2017) Magalhães,LG ; Telmo Oliveira Adão ; Emanuel Peres Correia