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A Developmental Learning Approach of Mobile Manipulator via Playing

机译:通过玩耍的移动机械手的发展学习方法

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摘要

Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode. By doing so, the robot gradually achieves it developmental goals by playing different modes of games. In the experiment, the game was instantiated into a mobile robot with the playing task of picking up toys, and the game is designed with a simple game mode and a complex game mode. A developmental algorithm, “Lift-Constraint, Act and Saturate,” is employed to drive the mobile robot move from the simple mode to the complex one. The experimental results show that the mobile manipulator is able to successfully learn the mobile grasping ability after playing simple and complex games, which is promising in developing robotic abilities to solve complex tasks using games.
机译:受婴儿发育理论的启发,本文提出了一种结合游戏元素的机器人发育模型。该模型不需要为机器人定义特定的开发目标,但是开发目标隐含在一系列游戏任务的目标中。根据游戏任务从简单到复杂的复杂性,游戏被划分为一系列的游戏模式,而任务的复杂性则取决于发展约束的应用。在给定当前模式的情况下,当机器人在当前模式下找不到任何新的显着刺激时,它将切换为以更复杂的游戏模式进行游戏。通过这样做,机器人通过玩不同的游戏模式逐渐达到其发展目标。在实验中,将游戏实例化为具有拾取玩具的游戏任务的移动机器人,并且将游戏设计为具有简单游戏模式和复杂游戏模式。开发算法“提升约束,作用和饱和”被用来驱动移动机器人从简单模式过渡到复杂模式。实验结果表明,该移动机械手在玩简单复杂的游戏后能够成功学习移动的抓地能力,这有望发展机器人的能力来解决游戏中的复杂任务。

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