Browsing by Author "Bogh, Simon"
Now showing items 1-6 of 6
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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 ... -
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 ... -
Novel automated interactive reinforcement learning framework with a constraint-based supervisor for procedural tasks
Elguea Aguinaco, Iñigo; 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 ... -
A review on reinforcement learning for contact-rich robotic manipulation tasks
Elguea, Íñigo; Arana-Arexolaleiba, Nestor; Serrano Muñoz, Antonio (Elsevier, 2023)Research and application of reinforcement learning in robotics for contact-rich manipulation tasks have exploded in recent years. Its ability to cope with unstructured environments and accomplish hard-to-engineer behaviors ... -
A Scalable and Unified Multi-Control Framework for KUKA LBR iiwa Collaborative Robots
Serrano Muñoz, Antonio; Elguea, Íñigo; Arana-Arexolaleiba, Nestor (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 ... -
skrl: Modular and Flexible Library for Reinforcement Learning
Arana-Arexolaleiba, Nestor (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 ...
