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Título

Active learning of manipulation sequences

AutorMartínez, David ; Alenyà, Guillem ; Jiménez Schlegl, Pablo; Torras, Carme; Rossmann, Jürgen; Wantia, Nils; Aksoy, Eren Erdal; Haller, Simon; Piater, Justus
Fecha de publicación2014
EditorInstitute of Electrical and Electronics Engineers
CitaciónIEEE International Conference on Robotics and Automation: 5671-5678 (2014)
ResumenWe 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 in the sense that the system tests actions to maximize learning progress and asks the teacher if needed. The main component is a symbolic planning engine that operates on learned rules, defined by actions and their pre- and postconditions. Learned by model-based reinforcement learning, rules are immediately available for planning. Thus, there are no distinct learning and application phases. We show how dynamic plans, replanned after every action if necessary, can be used for automatic execution of manipulation sequences, for monitoring of observed manipulation sequences, or a mix of the two, all while extending and refining the rule base on the fly. Quantitative results indicate fast convergence using few training examples, and highly effective teacher intervention at early stages of learning.
DescripciónTrabajo presentado al ICRA 2014 celebrado en Hong Kong del 31 de mayo al 7 de junio.
Versión del editorhttp://dx.doi.org/10.1109/ICRA.2014.6907693
URIhttp://hdl.handle.net/10261/127300
DOI10.1109/ICRA.2014.6907693
Identificadoresissn: 1050-4729
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