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Iterative affordance learning with adaptive action generation

Carlos Maestre 1 Ghanim Mukhtar 1 Christophe Gonzales 2 Stephane Doncieux 1, 3
2 DECISION
LIP6 - Laboratoire d'Informatique de Paris 6
3 AMAC
ISIR - Institut des Systèmes Intelligents et de Robotique
Abstract : A robot designer can provide a robot with knowledge to perform tasks on an environment. However, this approach can limit the achievement of future tasks executed by the robot. Providing it with the ability to develop its own skills paves the way for robots that are not limited by design. In this work a task consists in reproducing a given set of effects on an object. A robot must accomplish this task with limited information about the object, learning affordances to reproduce the effects, increasing this information throughout consecutive interactions with the object. We propose a method named Adaptive Affor-dance Learning (A 2 L) which endows a robot with the capacity to learn affordances associated to an object, both adapting the robot's actions to the object position, and increasing the robot's information about the object when needed. This paper presents two main contributions: first, an online adaption of the robot actions to interact with the object, decomposing each action into a sequence of movements, adapting each movement, in a close loop, to the object position; and second, to increase the information about the object, we propose an iterative process that alternates between (1) exploration of the environment interacting with the object, (2) affordance acquisition and (3) affordance validation. These contributions are assessed in two experiments where a simulated Baxter robot learns to push a box to different positions on a table.
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https://hal.archives-ouvertes.fr/hal-01617793
Contributor : Carlos Maestre <>
Submitted on : Tuesday, October 17, 2017 - 10:05:21 AM
Last modification on : Friday, January 8, 2021 - 5:32:07 PM
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  • HAL Id : hal-01617793, version 1

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Carlos Maestre, Ghanim Mukhtar, Christophe Gonzales, Stephane Doncieux. Iterative affordance learning with adaptive action generation. International Conference on Development and Learning (ICDL) and the International Conference on Epigenetic Robotics (EpiRob), Sep 2017, Lisbon, Portugal. ⟨hal-01617793⟩

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