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
Correia, D; Silva, MF; Moreira, AP;
Publication
2022 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)
Abstract
Teleoperation of autonomous mobile robots (AMR) is relevant in logistics operations to automate repetitive tasks that often result in injuries to the operator. This paper presents an overview of the systems involved in the current teleoperation scheme where these AMRs are present as well as some works and advances that have been done in the high-level teleoperation field.
2022
Authors
Sousa, RB; Rocha, C; Mendonca, HS; Moreira, AP; Silva, MF;
Publication
IEEE ACCESS
Abstract
The technological market is increasingly evolving as evidenced by the innovative and streamlined manufacturing processes. Printed Circuit Boards (PCB) are widely employed in the electronics fabrication industry, resorting to the Gerber open standard format to transfer the manufacturing data. The Gerber format describes not only metadata related to the manufacturing process but also the PCB image. To be able to map the electronic circuit pattern to be printed, a parser to convert Gerber files into a bitmap image is required. The current literature as well as available Gerber viewers and libraries showed limitations mainly in the Gerber format support, focusing only on a subset of commands. In this work, the development of a recursive descent approach for parsing Gerber files is described, outlining its interpretation and the renderization of 2D bitmap images. All the defined commands in the specification based on Gerber X2 generation were successfully rendered, unlike the tested commercial parsers used in the experiments. Moreover, the obtained results were comparable to those parsers regarding the commands they can execute as well as the ground-truth, emphasizing the accuracy of the proposed approach. Its top-down and recursive architecture allows easy integration with other software regardless of the platform, highlighting its potential inclusion and integration in the production of electronic circuits.
2022
Authors
Ferreira, P; Malheiro, B; Silva, M; Borges Guedes, P; Justo, J; Ribeiro, C; Duarte, A;
Publication
EDULEARN Proceedings - EDULEARN22 Proceedings
Abstract
2022
Authors
Ferreira, P; Malheiro, B; Silva, M; Borges Guedes, P; Justo, J; Ribeiro, C; Duarte, A;
Publication
EDULEARN Proceedings - EDULEARN22 Proceedings
Abstract
2022
Authors
Silva, M;
Publication
Journal of Artificial Intelligence and Technology
Abstract
[No abstract available]
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