Now showing items 1-13 of 13

    • Active learning of manipulation sequences 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Jimenez Schlegl, Pablo; Torras, Carme; Rossmann, Jürgen; Wantia, Nils; Eren Erdal, Aksoy; Haller, Simon; Piater, Justus (2014)
      Conference report
      Open Access
      We describe a system allowing a robot to learn goal-directed manipulation sequences such as steps of an assembly task. Learning is based on a free mix of exploration and instruction by an external teacher, and may be active ...
    • Finding safe policies in model-based active learning 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (2014)
      Conference report
      Open Access
      Task learning in robotics is a time-consuming process, and model-based reinforcement learning algorithms have been proposed to learn with just a small amount of experiences. However, reducing the number of experiences used ...
    • Influencia de parámetros de proceso en los valores de LW / SW de pieza pintada 

      Martínez Martínez, David (Universitat Politècnica de Catalunya, 2019-01-17)
      Bachelor thesis
      Open Access
      Covenantee:   SEAT S.A.
      Este proyecto tiene el objetivo de optimizar la producción de piezas pintadas de la empresa Plastic Omnium S.A ., específicamente de los modelos de parachoques delanteros de la marca SEAT . Se centra en estudiar las causas ...
    • Learning probabilistic action models from interpretation transitions 

      Martínez Martínez, David; Ribeiro, Tony; Inoue, Katsumi; Alenyà Ribas, Guillem; Torras, Carme (2015)
      Conference report
      Open Access
      Probabilistic planners are very flexible tools that provide good solutions for difficult tasks. However, they rely on a model of the domain and actions, which they have difficulties to learn for complex tasks. We propose ...
    • Learning relational dynamics of stochastic domains for planning 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme; Ribeiro, Tony; Inoue, Katsumi (2016)
      Conference report
      Open Access
      Probabilistic planners are very flexible tools that can provide good solutions for difficult tasks. However, they rely on a model of the domain, which may be costly to either hand code or automatically learn for complex ...
    • Learning relational models with human interaction for planning in robotics 

      Martínez Martínez, David (Universitat Politècnica de Catalunya, 2017-02-21)
      Doctoral thesis
      Open Access
      Automated planning has proven to be useful to solve problems where an agent has to maximize a reward function by executing actions. As planners have been improved to salve more expressive and difficult problems, there is ...
    • Manipulation monitoring and robot intervention in complex manipulation sequences 

      Savarimuthu, Thiusius Rajeeth; Buch, Anders G.; Yang, Yang; Mustafar, Wail; Haller, Simon; Papon, Jeremie; Martínez Martínez, David; Eren Erdal, Aksoy (2014)
      Conference report
      Open Access
      Compared to machines, humans are intelligent and dexterous; they are indispensable for many complex tasks in areas such as flexible manufacturing or scientific experimentation. However, they are also subject to fatigue and ...
    • Manipulation monitoring and robot intervention in complex manipulation sequences 

      Savarimuthu, Thiusius Rajeeth; Buch, Anders G.; Yang, Yang; Mustafar, Wail; Haller, Simon; Papon, Jeremie; Martínez Martínez, David; Eren Erdal, Aksoy (2014)
      Conference report
      Open Access
      Compared to machines, humans are intelligent and dexterous; they are indispensable for many complex tasks in areas such as flexible manufacturing or scientific experimentation. However, they are also subject to fatigue and ...
    • Planning robot manipulation to clean planar surfaces 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (2015)
      Article
      Open Access
      This paper presents a new approach to plan high-level manipulation actions for cleaning surfaces in household environments, like removing dirt from a table using a rag. Dragging actions can change the distribution of dirt ...
    • Planning surface cleaning tasks by learning uncertain drag actions outcomes 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (2013)
      Conference report
      Open Access
      A method to perform cleaning tasks is presented where a robot manipulator autonomously grasps a textile and uses different dragging actions to clean a surface. Ac- tions are imprecise, and probabilistic planning is ...
    • Relational reinforcement learning with guided demonstrations 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (2017)
      Article
      Open Access
      Model-based reinforcement learning is a powerful paradigm for learning tasks in robotics. However, in-depth exploration is usually required and the actions have to be known in advance. Thus, we propose a novel algorithm ...
    • Safe robot execution in model-based reinforcement learning 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (Institute of Electrical and Electronics Engineers (IEEE), 2015)
      Conference report
      Open Access
      Task learning in robotics requires repeatedly executing the same actions in different states to learn the model of the task. However, in real-world domains, there are usually sequences of actions that, if executed, may ...
    • V-MIN: efficient reinforcement learning through demonstrations and relaxed reward demands 

      Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme (2015)
      Conference report
      Restricted access - publisher's policy
      Reinforcement learning (RL) is a common paradigm for learning tasks in robotics. However, a lot of exploration is usually required, making RL too slow for high-level tasks. We present V-MIN, an algorithm that integrates ...