A Developmental Learning Approach of Mobile Manipulator via Playing.
A Developmental Learning Approach of Mobile Manipulator via Playing.
复制标题
移动机械手的游戏发展学习方法
DOI：
10.3389/fnbot.2017.00053
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发表时间：
2017
影响因子：
3.1
通讯作者：
Yang L
中科院分区：
文献类型：
--
作者：
Wu R;Zhou C;Chao F;Zhu Z;Lin CM;Yang L
受幼儿发展理论的启发，提出了一种结合游戏元素的机器人发展模型。该模型不需要为机器人定义特定的发展目标，但发展目标隐含在一系列游戏任务的目标中。根据游戏任务的复杂程度，将游戏划分为一系列的游戏模式，任务的复杂程度由发展约束的应用决定。给定当前模式，当机器人在当前模式中找不到任何新的显著刺激时，机器人切换到更复杂的游戏模式。通过这样做，机器人通过玩不同模式的游戏逐渐实现其发展目标。在实验中，游戏被实例化为一个移动的机器人，其游戏任务是捡玩具，游戏设计有简单的游戏模式和复杂的游戏模式。采用“升力约束、动作和饱和”的发展算法，驱动移动的机器人从简单模式向复杂模式运动。实验结果表明，移动的机械手能够在简单和复杂的游戏后成功地学习移动的抓取能力，这在利用游戏开发机器人解决复杂任务的能力方面具有很好的应用前景。
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.
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