Machine Learning in Robotics
Abstract
Robots act in a multimodal world and have to cope with increasingly complex tasks. These tasks have been usually dealt with using action rules and hand-crafted knowledge. This, however, limits the generalization of robotic systems to different domains and applications. Machine Learning is thus nowadays playing an important role in Robotics. Applications of machine learning techniques allow a robot to acquire novel skills or to be able to adapt itself to its environment. Examples of robot skills that can be targeted by machine learning algorithms are locomotion, grasping, manipulation, human-robot adaptive interface, robot perception and vision and linguistic abilities.
Topics
Machine learning
Data mining
Behavior and motion
Adaptation
Classification
Organizers
Brígida Mónica Faria, Polytechnic of Porto (ESS - P.Porto), Portugal
Luis Merino, Pablo de Olavide University (UPO), Seville, Spain
Adrià Colomé Figueras, IRI, CSIC-UPC, Barcelona, Spain
Guillem Alenyà, IRI, CSIC-UPC, Barcelona, Spain
Program committee
Ana Lopes - University of Coimbra
Armando Sousa – Universidade do Porto
Fernando Caballero Benítez - University of Seville
João Fabro - Federal University of Technology - Paraná - UTFPR – Brazil
João Messias – Instituto Superior Técnico
Luis Paulo Reis – Universidade do Porto
Noé Pérez-Higueras - Pablo de Olavide University
Nuno Lau – Universidade de Aveiro