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首页> 外文会议>The Fourth joint IEEE international conferences on development and learning and epigenetic robotics >Effective transfer learning of affordances for household robots
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Effective transfer learning of affordances for household robots

机译：有效转移家用机器人的津贴

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摘要

Learning how to use functional objects is essential for robots that are to carry out household tasks. However, learning every object from scratch would be a very naive and time-consuming approach. In this paper, we propose transfer learning of affordances to reduce the number of exploratory actions needed to learn how to use a new object. Through embodied interaction with the object, the robot discovers the object's similarity to previously learned objects by comparing their shape features and spatial relations between object parts. The robot actively selects object parts along with parameterized actions and evaluates the effects on-line. We demonstrate through real-world experiments with the humanoid robot NAO that our method is able to speed up the use of a new type of garbage can by transferring the affordances learned previously for similar garbage cans.
机译：学习如何使用功能对象对于执行家庭任务的机器人至关重要。但是，从头开始学习每个对象将是一种非常幼稚且耗时的方法。在本文中，我们提出转移能力的学习，以减少学习如何使用新对象所需的探索性行动的数量。通过与对象的具体交互，机器人通过比较对象的形状特征和对象部分之间的空间关系，发现对象与先前学习的对象的相似性。机器人会主动选择对象零件以及参数化的动作，并在线评估效果。通过人形机器人NAO的真实实验，我们证明了我们的方法能够通过转移以前为类似垃圾桶学到的补贴来加速新型垃圾桶的使用。

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