Visuo-motor learning for face-to-face pass between heterogeneous humanoids
Visuo-motor learning for face-to-face pass between heterogeneous humanoids
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DOI：
10.1016/j.robot.2006.03.001
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发表时间：
2006-06
期刊：
影响因子：
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通讯作者：
M. Ogino;Masaaki Kikuchi;M. Asada
中科院分区：
文献类型：
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作者：
M. Ogino;Masaaki Kikuchi;M. Asada
由于其结构复杂、自由度大，类人行为生成是最棘手的问题之一。针对这一问题，本文提出了一种仿人机器人控制器。首先将给定的任务分解为一系列模块，每个模块由一组具有控制参数的模块原语组成，以实现相应的原语动作。然后，通过视觉信息（流）和运动命令之间的感觉运动映射来学习这些参数。控制器通过选择一个模块、被选择模块中的模块原语以及预先学习到的相应的控制参数来完成给定的任务。在RoboCup比赛中选择面对面传球作为示例任务。（据我们所知，这是第一次试验。）相应的模块是接近一个球，将球踢给对手，以及将球截住。为了证明该方法的有效性，将该方法分别应用于两个不同的人形机器人，并成功地实现了3轮以上的面对面通过。
Humanoid behavior generation is one of the most formidable issues due to its complicated structure with many degrees of freedom. This paper proposes a controller for a humanoid to cope with this issue. A given task is decomposed into a sequence of modules first, each of which consists of a set of module primitives that have control parameters to realize the appropriate primitive motions. Then, these parameters are learned by sensorimotor maps between visual information (flow) and motor commands. The controller accomplishes a given task by selecting a module, a module primitive in the selected module, and its appropriate control parameters learned in advance. A face-to-face ball pass in a RoboCup context is chosen as an example task. (To the best of our knowledge, this is the first trial.) The corresponding modules are approaching a ball, kicking a ball to the opponent, and trapping a ball coming to the player. In order to show the validity, the method is applied to two different humanoids, independently, and they succeed in realizing the face-to-face pass for more than three rounds.