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Teaching Robots New Actions through Natural Language Instructions

Lanbo She, Yu Cheng, Joyce Chai, Yunyi Jia, Shaohua Yang, Ning Xi

发表年份
2014
引用次数
77

摘要

Robots often have limited knowledge and need to continuously acquire new knowledge and skills in order to collaborate with its human partners. To address this issue, this paper describes an approach which allows human partners to teach a robot (i.e., a robotic arm) new high-level actions through natural language instructions. In particular, built upon the traditional planning framework, we propose a representation of high-level actions that only consists of the desired goal states rather than step-by-step operations (although these operations may be specified by the human in their instructions). Our empirical results have shown that, given this representation, the robot can reply on automated planning and immediately apply the newly learned action knowledge to perform actions under novel situations.

关键词

Computer scienceRobotNatural languageRepresentation (politics)Human–computer interactionAction (physics)Artificial intelligenceHuman–robot interactionKnowledge representation and reasoningNatural (archaeology)

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