Now showing items 1-20 of 28

    • A competitive strategy for function approximation in Q-learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2011)
      Conference report
      Open Access
      In this work we propose an approach for generalization in continuous domain Reinforcement Learning that, instead of using a single function approximator, tries many different function approximators in parallel, each one ...
    • A Legendre-Gauss pseudospectral collocation method for trajectory optimization in second order systems 

      Moreno Martín, Siro; Ros Giralt, Lluís; Celaya Llover, Enric (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      Pseudospectral collocation methods have proven to be powerful tools to solve optimal control problems. While these methods generally assume the dynamics is given in the first order form xdot = f(x, u, t), where x is the ...
    • A relational positioning methodology for robot task specification and execution 

      Rodríguez Tsouroukdissian, Adolfo; Basañez Villaluenga, Luis; Celaya Llover, Enric (IEEE, 2008)
      Article
      Open Access
      This paper presents a relational positioning methodology that allows to restrict totally or partially the movements of an object by specifying its allowed positions in terms of a set of intuitive geometric constraints. In ...
    • Action rule induction from cause-effect pairs learned through robot-teacher interaction 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (University of Karlsruhe, 2008)
      Conference report
      Open Access
      In this work we propose a decision-making system that efficiently learns behaviors in the form of rules using natural human instructions about cause-effect relations in currently observed situations, avoiding complicated ...
    • Action rule induction from cause-effect pairs learned through robot-teacher interaction 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (2008)
      Conference report
      Open Access
      In this work we propose a decision-making system that efficiently learns behaviors in the form of rules using natural human instructions about cause-effect relations in currently observed situations, avoiding complicated ...
    • Collocation methods for second and higher order systems 

      Moreno Martín, Siro; Ros Giralt, Lluís; Celaya Llover, Enric (2023-02-01)
      Article
      Open Access
      It is often unnoticed that the predominant way to use collocation methods is fundamentally flawed when applied to optimal control in robotics. Such methods assume that the system dynamics is given by a first order ODE, ...
    • Collocation methods for second order systems 

      Moreno Martín, Siro; Ros Giralt, Lluís; Celaya Llover, Enric (2022)
      Conference report
      Open Access
      Collocation methods for numerical optimal control commonly assume that the system dynamics is expressed as a first order ODE of the form x¿ = f(x, u, t), where x is the state and u the control vector. However, in many ...
    • Competitive function approximation for reinforcement learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2014)
      Research report
      Open Access
      The application of reinforcement learning to problems with continuous domains requires representing the value function by means of function approximation. We identify two aspects of reinforcement learning that make the ...
    • Description of a robotics-oriented relational positioning methodology 

      Rodríguez Tsouroukdissian, Adolfo; Basañez Villaluenga, Luis; Celaya Llover, Enric (2007-09)
      Research report
      Open Access
      This paper presents a relational positioning methodology for flexibly and intuitively specifying offline programmed robot tasks, as well as for assisting the execution of teleoperated tasks demanding precise movements. In ...
    • Exact interval propagation for the efficient solution of planar linkages 

      Celaya Llover, Enric; Creemers, Tom Lambert; Ros Giralt, Lluís (ASME, 2007)
      Conference report
      Open Access
      This paper presents an interval propagation algorithm for variables in single-loop linkages. Given allowed intervals of values for all variables, the algorithm provides, for every variable, the exact interval of values for ...
    • Exact interval propagation for the efficient solution of position analysis problems on planar linkages 

      Celaya Llover, Enric; Creemers, Tom Lambert; Ros Giralt, Lluís (2012)
      Article
      Open Access
      This paper presents an interval propagation algorithm for variables in planar single-loop linkages. Given intervals of allowed values for all variables, the algorithm provides, for every variable, the whole set of values, ...
    • Learning rules from cause-effects explanations 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (2008)
      Research report
      Open Access
      In this work we propose a learning system to learn on-line an action policy coded in rules using natural human instructions about cause-effect relations in currently observed situations. The instructions only on currently ...
    • Model predictive control for a Mecanum-wheeled robot navigating among obstacles 

      Moreno Caireta, Iñigo; Celaya Llover, Enric; Ros Giralt, Lluís (Elsevier, 2021)
      Conference report
      Open Access
      Mecanum-wheeled robots have been thoroughly used to automate tasks in many different applications. However, they are usually controlled by neglecting their dynamics and relying only on their kinematic model. In this paper, ...
    • Natural landmark detection for visually-guided robot navigation 

      Celaya Llover, Enric; Albarral, José L.; Jiménez Schlegl, Pablo; Torras, Carme (Springer, 2007)
      Part of book or chapter of book
      Open Access
      The main difficulty to attain fully autonomous robot navigation outdoors is the fast detection of reliable visual references, and their subsequent characterization as landmarks for immediate and unambiguous recognition. ...
    • Natural landmark detection for visually-guided robot navigation 

      Celaya Llover, Enric; Albarral Garcia, Jose Luis; Jiménez Schlegl, Pablo; Torras, Carme (2007)
      Conference report
      Open Access
      The main difficulty to attain fully autonomous robot navigation outdoors is the fast detection of reliable visual references, and their subsequent characterization as landmarks for immediate and unambiguous recognition. ...
    • On-line learning of macro planning operators using probabilistic estimations of cause-effects 

      Agostini, Alejandro Gabriel; Wörgötter, Florentin; Celaya Llover, Enric; Torras, Carme (2008)
      Research report
      Open Access
      In this work we propose an on-line learning method for learning action rules for planning. The system uses a probabilistic approach of a constructive induction method that combines a beam search with an example-based search ...
    • Online EM with weight-based forgetting 

      Celaya Llover, Enric; Agostini, Alejandro Gabriel (2015)
      Article
      Open Access
      In the on-line version of the EM algorithm introduced by Sato and Ishii (2000), a time-dependent discount factor is introduced for forgetting the effect of the old posterior values obtained with an earlier, inaccurate ...
    • Online reinforcement learning using a probability density estimation 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (The MIT Press. Massachusetts Institute of Technology, 2017-01-01)
      Article
      Open Access
      Function approximation in online, incremental, reinforcement learning needs to deal with two fundamental problems: biased sampling and nonstationarity. In this kind of task, biased sampling occurs because samples are ...
    • Probability density estimation of the Q Function for reinforcement learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2009)
      Research report
      Open Access
      Performing Q-Learning in continuous state-action spaces is a problem still unsolved for many complex applications. The Q function may be rather complex and can not be expected to fit into a predefined parametric model. In ...