自然语言训练的机器人基本行为控制器

ROBOT MOTION BEHAVIOR TRAINING BY NATURAL LANGUAGE INSTRUCTIONS

  • 摘要: 本文探索了一种直接利用自然语言进行机器人运动技能训练的控制方法,提出了利用模糊神经网络结构作为基本行为控制单元,通过教师的自然语言指令完成针对某一特定行为的运动经验获取和控制器训练,这是一种更加自然的控制器构造方式,以基本运动单元为基础,可以进一步实现机器人复杂任务的语言编程与控制.所提控制方法最终在一个轮式移动机器人系统上进行了语言训练实验.

     

    Abstract: A control method that trains robot to learn motion skills by natural language is explored in this paper, where fuzzy neural networks are used as a general structure of controller for different motion primitives. For any specified motion primitives, the controller acquires knowledge and is trained by instructions of natural language from a supervisor. This might be a more natural way to construct a motion controller. Based on the trained motion primitives, more complex motion tasks can be implemented. Experiments on natural language training for motion primitives have been done on a wheeled robot.

     

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