Search
Now showing items 1-10 of 18
FlexRQC: Model for a Flexible Robot-Driven Quality Control Station
(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 ...
skrl: Modular and Flexible Library for Reinforcement Learning
(ArXiv, 2022)
skrl is an open-source modular library for reinforcement learning written in Python and designed with a focus on readability, simplicity, and transparency of algorithm implementations. Apart from supporting environments ...
Goal-Conditioned Reinforcement Learning within a Human-Robot Disassembly Environment
(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 ...
Fear Field: Adaptive constraints for safe environment transitions in Shielded Reinforcement Learning
(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 ...
Learning and generalising object extraction skill for contact-rich disassembly tasks: an introductory study
(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 ...
Shielded Reinforcement Learning: A review of reactive methods for safe learning
(IEEE, 2023)
Reinforcement Learning (RL) algorithms are showing promising results in simulated environments, but their replication in real physical applications, even more so in safety-critical applications, is not yet guaranteed. ...
A Scalable and Unified Multi-Control Framework for KUKA LBR iiwa Collaborative Robots
(IEEE, 2023)
The trend towards industrialization and digitalization has led more and more companies to deploy robots in their manufacturing facilities. In the field of collaborative robotics, the KUKA LBR iiwa is one of the benchmark ...
Labor Induction failure prediction using Gabor filterbanks and Center Symmetric Local Binary Patterns
(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 ...
Labor Induction failure prediction based on B-Mode Ultrasound Image Processing using Multiscale Local Binary Patterns
(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 ...
Evaluación de la experiencia de uso de un entorno robótico industrial en realidad virtualEvaluation of the user experience of an industrial robotic environment in virtual reality
(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 ...
