2022
Authors
Magalhães, SC; dos Santos, FN; Machado, P; Moreira, AP; Dias, J;
Publication
CoRR
Abstract
2022
Authors
Santos, LC; Santos, FN; Aguiar, AS; Valente, A; Costa, P;
Publication
2022 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)
Abstract
Robotics will play an essential role in agriculture. Deploying agricultural robots on the farm is still a challenging task due to the terrain's irregularity and size. Optimal path planning solutions may fail in larger terrains due to memory requirements as the search space increases. This work presents a novel open-source solution called AgRob Topologic Path Planner, which is capable of performing path planning operations using a hybrid map with topological and metric representations. A local A* algorithm pre-plans and saves local paths in local metric maps, saving them into the topological structure. Then, a graph-based A* performs a global search in the topological map, using the saved local paths to provide the full trajectory. Our results demonstrate that this solution could handle large maps (5 hectares) using just 0.002 % of the search space required by a previous solution.
2022
Authors
Cordeiro, A; Rocha, LF; Costa, C; Costa, P; Silva, MF;
Publication
2022 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)
Abstract
Bin picking is a highly researched topic, due to the need for automated procedures in industrial environments. A general bin picking system requires a highly structured process, starting with data acquisition, and ending with pose estimation and grasping. A high number of bin picking problems are being presently solved, through deep learning networks, combined with distinct procedures. This study provides a comprehensive review of deep learning approaches, implemented in bin picking problems. Throughout the review are described several approaches and learning methods based on specific domains, such as gripper oriented and object oriented, as well as summarized several methodologies, in order to solve bin picking issues. Furthermore, are introduced current strategies used to simplify particular cases and at last, are presented peculiar means of detecting object poses.
2022
Authors
Piardi, L; Leitão, P; Costa, P; de Oliveira, AS;
Publication
Studies in Computational Intelligence
Abstract
Cyber-Physical Systems (CPS) transform traditional systems into a network of connected and heterogeneous systems, integrating computational and physical elements, that works as a complex system whose overall properties are greater than the sum of its parts. However, CPS is not free from faulty episodes and their consequences such as malfunctions, breakdowns, and service interruption. Traditional centralized models for fault-tolerance do not meet the complexity of the current industrial scenarios and particularly the industrial CPS requirements. Having this in mind, this work presents a holonic-based architecture to address the fault-tolerance in CPS by distributing the detection, diagnosis, and recovery in the local individual entities and also considers the emergent behaviour resulting from the collaboration of these entities. An experimental case study is used to illustrate the potential application of the fault-tolerant approach. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
2022
Authors
Piardi, L; Costa, P; Oliveira, A; Leitao, P;
Publication
Proceedings of the IEEE International Conference on Industrial Technology
Abstract
Industrial Cyber-Physical Systems (ICPS) deploy a network of connected and heterogeneous systems, integrating computational and physical components, improving production and quality. However, a fault-free system is still utopian, but methodologies related to fault detection and diagnosis are still being treated in isolation or a centralized approach, overlooking the technological advances related to ICPS such as IoT, AI and edge computing. With this in mind, the present work proposes a collaborative architecture for fault detection and diagnosis, regarding the exchange of information for collaborative detection and diagnosis adopting disruptive technologies. Laboratory-scale ICPS experiments were carried out to compare the proposed approach with the approach where each component separately intends to identify and diagnose faults. The results present a faster response generating a system more flexible and robust. © 2022 IEEE.
2022
Authors
Alvarez, M; Brancaliao, L; Gomes, D; Pinto, V; Carneiro, J; Santos, J; Coelho, JP; Goncalves, J;
Publication
CONTROLO 2022
Abstract
This paper presents a first prototype of an automated system that will be applied in stoneware tableware ceramics finishing, being developed in the scope of STC 4.0 HP project. The main objective of this prototype is to test different alternatives to obtain a precise finish on ceramic pieces produced by GRESTEL - PRODUTOS CERAMICOS S.A, improving the production of irregular pieces that until now are finished using manual labor. This is why the implementation of a closedloop control of the rotation speed of a finishing sponge and its applied force control is proposed. The mechanical structure of the devised solution was prototyped using a FDM based technology. A 3D printer was used for the manufacturing of the structural parts to support the rotating sponge and measurement sensors. In addition a PID based control is used to control the system. Once the prototype has been designed and assembled a series of tests and measurements were carried out leading to the conclusion that the proposed approach is adequate to meet the design requirements for this prototype.
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