Learning the Affordances of Tools Using a Behavior-Grounded Approach
Learning the Affordances of Tools Using a Behavior-Grounded Approach
复制标题
使用基于行为的方法学习工具的可供性
DOI：
10.1007/978-3-540-77915-5_10
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Alexander Stoytchev
中科院分区：
文献类型：
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作者：
Alexander Stoytchev
本文介绍了一种基于行为的方法来表示和学习机器人工具的可供性。可供性表示是在行为咿呀学语阶段学习的，在该阶段机器人随机选择不同的探索行为，将它们应用到工具中，并观察它们对环境对象的影响。作为这一探索过程的结果，工具表示以机器人的行为和感知能力为基础。此外，该表示可以由机器人自主测试和验证，因为它是用机器人控制器直接可用的具体术语（即行为）来表达的。这里描述的工具表示还可以用于通过动态排序探索行为来解决使用工具的任务，这些探索行为用于根据预期结果探索工具。使用严格的工具在延伸任务中测试了学习到的表示的质量。
This paper introduces a behavior-grounded approach to representing and learning the affordances of tools by a robot. The affordance representation is learned during a behavioral babbling stage in which the robot randomly chooses different exploratory behaviors, applies them to the tool, and observes their effects on environmental objects. As a result of this exploratory procedure, the tool representation is grounded in the behavioral and perceptual repertoire of the robot. Furthermore, the representation is autonomously testable and verifiable by the robot as it is expressed in concrete terms (i.e., behaviors) that are directly available to the robot's controller. The tool representation described here can also be used to solve tool-using tasks by dynamically sequencing the exploratory behaviors which were used to explore the tool based on their expected outcomes. The quality of the learned representation was tested on extension-of-reach tasks with rigid tools.
DOI：
10.1109/jra.1987.1087109
发表时间：
1987-08-01
期刊：
IEEE JOURNAL OF ROBOTICS AND AUTOMATION
影响因子：
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作者：
TSAI, RY
通讯作者：
TSAI, RY