Sigma-Delta Networks for Robot Arm Control

W. Lawson, Anthony M. Harrison, J. Trafton
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Abstract

Our autonomous robot, Bight, can be a reliable teammate that is capable of assisting in performing routine maintenance tasks on a Naval vessel. In this paper, we consider the task of maintaining the electrical panel. A vital first step is putting the robot into the correct position to view all of the parts of the electrical panel. The robot can get close, but the arm of the robot will need to move to where it can see everything. Here, we propose to solve this using a sigma delta spiking network that is trained using deep Q learning. Our approach is able to successfully solve this problem at varying distances. While we show how this works on this specific problem, we believe this approach to be general enough to be applied to any similar problem.
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机器人手臂控制的Sigma-Delta网络
我们的自主机器人Bight可以成为一个可靠的队友,能够协助执行海军舰艇的日常维护任务。在本文中,我们考虑的任务是维护电气面板。至关重要的第一步是将机器人放置在正确的位置,以查看电气面板的所有部件。机器人可以靠近,但机器人的手臂需要移动到它能看到一切的地方。在这里,我们建议使用使用深度Q学习训练的sigma delta尖峰网络来解决这个问题。我们的方法能够在不同的距离上成功地解决这个问题。虽然我们展示了这种方法在这个特定问题上的工作原理,但我们认为这种方法足够通用,可以应用于任何类似的问题。
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