Listar por autor "caed28184827c7bfcd3727737b5ba7c2"
Mostrando ítems 1-20 de 26
-
3D inspection methods for specular or partially specular surfaces
Maestro-Watson, Daniel (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2020)Deflectometric techniques are a powerful tool for the automated quality control of specular or shiny surfaces. These techniques are based on using a camera to observe a reference pattern reflected on the surface under ... -
Application of artificial intelligence techniques to the smart control of sheet metal forming processes
Sáenz de Argandoña, Eneko (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2009)The present research work aims at evaluating the economical feasibility and the technological viability of implementing intelligent control systems in complex industrial manufacturing processes; in this case forming ... -
Application of Computer Vision and Deep Learning in the railway domain for autonomous train stop operation
Arana-Arexolaleiba, Nestor (IEEE, 2020)The purpose of this paper is to present the results of the analysis of the application of Deep Learning in the railway domain with a particular focus on a train stop operation. The paper proposes an approach consisting of ... -
Calibración de sistemas de triangulación láser basados en cámaras Scheimpflug
Legarda Cristobal, Aritz (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2015)The continuous improvement that exists in the economy, leads to generate new processes, new products or new concepts. Thanks to the continuous improvement mentioned before, the manufacturing industry has developed new ... -
Computer vision techniques for autonomous vehicles applied to urban underground railway
Etxeberria Garcia, Mikel (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2022)Autonomous vehicles’ presence is becoming a reality in everyday life, with autonomous driving cars on the road, GOA3-GOA4 trains in the railway domain, or automated guided vehicles in the industrial domain. These autonomous ... -
Deflectometric data segmentation for surface inspection: a fully convolutional neural network approach
Maestro-Watson, Daniel; Balzategui, Julen; Eciolaza, Luka; Arana-Arexolaleiba, Nestor (SPIE, 2020)The purpose of this paper is to explore the use of fully convolutional neural networks (FCN) to perform a semantic segmentation of deflectometric recordings for quality control of reflective surfaces. The proposed method ... -
Evaluación de la experiencia de uso de un entorno robótico industrial en realidad virtual
Apraiz, Ainhoa; Lasa, Ganix; Arana-Arexolaleiba, Nestor; Serrano Muñoz, Antonio; Elguea, Íñigo (AEIPRO, 2022)Industry 4.0 is leading to a whole new level of process automation, thus redefining the role of humans, and altering existing jobs in yet unknown ways. Although the number of robots in the manufacturing industry has been ... -
Fear Field: Adaptive constraints for safe environment transitions in Shielded Reinforcement Learning
Odriozola Olalde, Haritz; Arana-Arexolaleiba, Nestor (CEUR-WS.org, 2023)Shielding methods for Reinforcement Learning agents show potential for safety-critical industrial applications. However, they still lack robustness on nominal safety, a key property for safety control systems. In the case ... -
FlexRQC: Model for a Flexible Robot-Driven Quality Control Station
González Tomé, Ander; Irigoyen Ceberio, Ibai; Ayala, Unai; Agirre, Joseba Andoni; Arana-Arexolaleiba, Nestor (Elsevier Ltd., 2020)As the investment on a dedicated quality control stations is not desirable for limited production batches. In general, those systems result in very optimised systems and the lack of flexibility since they are designed for ... -
Goal-Conditioned Reinforcement Learning within a Human-Robot Disassembly Environment
Arana-Arexolaleiba, Nestor (MDPI, 2022)The introduction of collaborative robots in industrial environments reinforces the need to provide these robots with better cognition to accomplish their tasks while fostering worker safety without entering into safety ... -
Human-Robot Interaction with Unimodal and Multimodal Interfaces: Dataset on performance, physiological response and user perception during a disassembly task
Apraiz, Ainhoa; Lasa, Ganix; Mazmela Etxabe, Maitane; Arana-Arexolaleiba, Nestor; Elguea, Íñigo; Escallada Lopez, Oscar; Osa Arzuaga, Nagore; Etxabe, Amaia (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2025) -
Image Enhancement using GANs for Monocular Visual Odometry
Zubieta Ansorregi, Jon; Etxeberria Garcia, Mikel; Zamalloa, Maider; Arana-Arexolaleiba, Nestor (IEEE, 2021)Drones, mobile robots, and autonomous vehicles use Visual Odometry (VO) to move around complex environments. ORB-SLAM or deep learning-based approaches like DF-VO are two of the state-of-the-art technics for monocular VO. ... -
Implementation analysis for a hybrid particle filter on an FPGA based smart camera
Zuriarrain Arcarazo, Iker; Arana-Arexolaleiba, Nestor (Scitepress, 2010)Design and development of embedded devices which perform computer vision related task presents many challenges, many of which stem from attempting to fit the complexity of many higher level vision algorithms into the ... -
Labor Induction failure prediction based on B-Mode Ultrasound Image Processing using Multiscale Local Binary Patterns
Arana-Arexolaleiba, Nestor; Izaguirre Altuna, Alberto (IEEE, 2016)Labor induction is defined as the artificial onset of labor for the purpose of vaginal birth. Cesarean section is one of the potential risks of labor induction as it occurs in about 20% of the inductions. A ripe cervix ... -
Labor Induction failure prediction using Gabor filterbanks and Center Symmetric Local Binary Patterns
Arana-Arexolaleiba, Nestor; Izaguirre Altuna, Alberto (IEEE, 2018)Labor induction is defined as the artificial stimulation of uterine contractions aimed to induce vaginal birth. Occurring in about 20% of pregnancies labor induction has become one the most commonly practiced procedures ... -
Learning and generalising object extraction skill for contact-rich disassembly tasks: an introductory study
Arana-Arexolaleiba, Nestor (Springer, 2021)Remanufacturing automation must be designed to be flexible and robust enough to overcome the uncertainties, conditions of the products, and complexities in the planning and operation of the processes. Machine learning ... -
Monocular visual odometry for underground railway scenarios
Etxeberria Garcia, Mikel; Labayen, Mikel; Eizaguirre, Fernando; Zamalloa, Maider; Arana-Arexolaleiba, Nestor (SPIE, 2021)In this paper, the application of monocular Visual Odometry (VO) solutions for underground train stopping operation are explored. In order to analyze if the application of monocular VO solutions in challenging environments as ... -
Novel automated interactive reinforcement learning framework with a constraint-based supervisor for procedural tasks
Elguea, Íñigo; Aguirre, Aitor; Izagirre, Unai; Inziarte Hidalgo, Ibai; Bogh, Simon; Arana-Arexolaleiba, Nestor (Elsevier, 2025)Learning to perform procedural motion or manipulation tasks in unstructured or uncertain environments poses significant challenges for intelligent agents. Although reinforcement learning algorithms have demonstrated positive ... -
Reinforcement Learning Approaches for Collaborative Robot Control in Manipulation Tasks
Elguea, Íñigo (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2024)With the exponential growth in technological advancement and the increasing reliance on electrical and electronic equipment, the efficient treatment of end-of-life products has become essential for mitigating environmental ... -
Reinforcement learning for collaborative robotic contact-rich disassembly tasks
Serrano Muñoz, Antonio (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2023)With the exponential growth of the world’s population and the resulting increase in consumption rates, the efficient treatment of end-of-life (EOL) products has become critical to mitigating environmental impacts. ...
