@conference {463, title = {UJI RobInLab{\textquoteright}s Approach to the Amazon Robotics Challenge 2017}, booktitle = {2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems}, year = {2017}, publisher = { IEEE Xplore}, organization = { IEEE Xplore}, address = {Daegu, Korea}, author = {Angel P. del Pobil and Majd Kassawat and Angel J Duran and Monica Arias and Nataliya Nechyporenko and Arijit Mallick and Enric Cervera and Dipendra Subedi and Ilia Vasilev and Daniel Cardin and Emanuele Sansebastiano and Ester Martinez-Martin and Antonio Morales and Gustavo A. Casa{\~n} and Alejandro Arenal and Bjorn Goriatcheff and Carlos Rubert and Gabriel Recatala} } @conference {482, title = {Discovering the Relationship Between the Morphology and the Internal Model in a Robot System by Means of Neural Networks}, booktitle = {International Conference on Intelligent Autonomous Systems}, year = {2016}, publisher = {Springer}, organization = {Springer}, author = {Angel J Duran and del Pobil, Angel P} } @conference {416, title = {Initial weight estimation for learning the internal model based on the knowledge of the robot morphology}, booktitle = {Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, author = {Angel J Duran and del Pobil, Angel P} } @conference {403, title = {A Model of Artificial Genotype and Norm of Reaction in a Robotic System}, booktitle = {International Conference on Simulation of Adaptive Behavior}, year = {2016}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, author = {Angel J Duran and Angel P. del Pobil} } @conference {347, title = {Adaptive Saccade Controller Inspired by the Primates{\textquoteright} Cerebellum}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2015}, month = {05/2015}, address = {Seattle, Washington, USA}, abstract = {
Saccades are fast eye movements that allow humans and robots to bring the visual target in the center of the visual field. Saccades are open loop with respect to the vision system, thus their execution require a precise knowledge of the internal model of the oculomotor system. In this work, we modeled the saccade control, taking inspiration from the recurrent loops between the cerebellum and the brainstem. In this model, the brainstem acts as a fixed-inverse model of the oculomotor system, while the cerebellum acts as an adaptive element that learns the internal model of the oculomotor system. The adaptive filter is implemented using a state-of-the- art neural network, called I-SSGPR. The proposed approach, namely recurrent architecture, was validated through experiments performed both in simulation and on an antropomorphic robotic head. Moreover, we compared the recurrent architecture with another model of the cerebellum, the feedback error learning. Achieved results show that the recurrent architecture outperforms the feedback error learning in terms of accuracy and insensitivity to the choice of the feedback controller.
11:20-11:24, Paper FrA2T5.6
}, keywords = {Biologically-Inspired Robots, Control Architectures and Programming, Learning and Adaptive Systems}, author = {Antonelli, Marco and Angel J Duran and Eris Chinellato and Angel P. del Pobil} } @conference {374, title = {Tombatossals: A humanoid torso for autonomous sensor-based tasks}, booktitle = {Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on}, year = {2015}, publisher = {IEEE}, organization = {IEEE}, author = {Felip, Javier and Angel J Duran and Antonelli, Marco and Morales, Antonio and Angel P. del Pobil} } @article {296, title = {A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot}, journal = {IEEE Trans. Auton. Mental Develop}, year = {2014}, pages = {1{\textendash}15}, doi = {10.1109/TAMD.2014.2332875}, author = {Marco Antonelli and Gibaldi, Agostino and Beuth, Frederik and Angel J Duran and Canessa, Andrea and Chessa, Manuela and Solari, F and Angel P. del Pobil and Hamker, F and Eris Chinellato and Sabatini, SP} } @article {Antonelli2014, title = {Learning the visual-oculomotor transformation: Effects on saccade control and space representation}, journal = {Robotics and Autonomous Systems}, year = {2014}, abstract = {

Active eye movements can be exploited to build a visuomotor representation of the surrounding environment. Maintaining and improving such representation requires to update the internal model involved in the generation of eye movements. From this perspective, action and perception are thus tightly coupled and interdependent. In this work, we encoded the internal model for oculomotor control with an adaptive filter inspired by the functionality of the cerebellum. Recurrent loops between a feed-back controller and the internal model allow our system to perform accurate binocular saccades and create an implicit representation of the nearby space. Simulations results show that this recurrent architecture outperforms classical feedback-error-learning in terms of both accuracy and sensitivity to system parameters. The proposed approach was validated implementing the framework on an anthropomorphic robotic head.

}, keywords = {Cerebellum, Gaussian process regression, Humanoid robotics, Sensorimotor transformation, stereo vision}, issn = {09218890}, doi = {10.1016/j.robot.2014.11.018}, url = {http://www.sciencedirect.com/science/article/pii/S092188901400311X}, author = {Marco Antonelli and Angel J Duran and Eris Chinellato and Angel P. del Pobil} } @proceedings {103, title = {Application of the Visuo-Oculomotor Transformation to Ballistic and Visually-Guided Eye Movements}, year = {2013}, author = {Marco Antonelli and Angel J Duran and Angel P. del Pobil} } @inbook {39, title = {Integration of Visuomotor Learning, Cognitive Grasping and Sensor-Based Physical Interaction in the UJI Humanoid Torso}, booktitle = {Designing Intelligent Robots: Reintegrating AI}, volume = {SS-13-04}, year = {2013}, pages = {pp. 6-11}, publisher = {AAAI}, organization = {AAAI}, isbn = {978-1-57735-601-1}, author = {Angel P. del Pobil and Angel J Duran and Marco Antonelli and Javier Felip and Antonio Morales and M. Prats and Eris Chinellato} } @inbook {102, title = {Speeding-Up the Learning of Saccade Control}, booktitle = {Biomimetic and Biohybrid Systems}, series = {Lecture Notes in Computer Science}, volume = {8064}, year = {2013}, pages = {12-23}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, isbn = {978-3-642-39801-8}, doi = {10.1007/978-3-642-39802-5_2}, url = {http://dx.doi.org/10.1007/978-3-642-39802-5_2}, author = {Marco Antonelli and Angel J Duran and Eris Chinellato and Angel P. del Pobil}, editor = {Lepora, NathanF. and Mura, Anna and Krapp, Holger G. and Paul F. M. J. Verschure and Tony J. Prescott} }