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首页> 外文会议>The Fourth joint IEEE international conferences on development and learning and epigenetic robotics >A neural dynamics to organize timed movement: Demonstration in a robot ball bouncing task
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A neural dynamics to organize timed movement: Demonstration in a robot ball bouncing task

机译：组织定时运动的神经动力学：在机器人弹跳任务中的演示

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To address how different movement behaviors may be timed to sensory events while being flexibly organized in sequence, we propose a neural dynamic model of timed movement organization. Two layers of neural dynamics control the activation and de-activation of different elementary movements, while a third layer uses stable limit cycle oscillators to generate timed movement trajectories. Both the organization and the generation of the timed movements are coupled to online sensory information so that the system can compensate for perturbations by updating the movement trajectory while recovering the required movement timing. We formulate and demonstrate the approach in a robotic ball bouncing task. When the ball begins to fall, the robot arm moves to the interception point in a plane and initiates a rotatory motion of the racket timed such as to hit the ball with maximal velocity. When the ball is no longer falling or falling outside the reachable space, the robot moves the racket back toward baseline. A physics simulation is used to assess themodel and demonstrate its capacity to handle perturbations of the ball trajectory.
机译：为了解决在依序灵活组织顺序运动时如何将不同的运动行为定时到感觉事件的问题，我们提出了定时运动组织的神经动力学模型。神经动力学的两层控制不同基本运动的激活和去激活，而第三层则使用稳定的极限循环振荡器来生成定时运动轨迹。定时运动的组织和生成都与在线感官信息相关，因此系统可以通过更新运动轨迹来补偿扰动，同时恢复所需的运动时间。我们制定并演示了自动球弹跳任务中的方法。当球开始掉落时，机械臂会移动到飞机上的拦截点，并开始定时进行球拍的旋转运动，以便以最大速度击球。当球不再掉入或掉落到可到达的空间之外时，机器人会将球拍移回基线。物理模拟用于评估模型并证明其处理球轨迹扰动的能力。

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