Taking inspiration from the navigation ability of humans, this study investigated a method of providing robotic controllers with a basic sense of position. It incorporated robotic simulators into robotic controllers to provide them with a mechanism to approximate the effects their actions had on the robot. Controllers with and without internal simulators were tested and compared. The proposed controller architecture was shown to outperform the regular controller architecture. However, the longer an internal simulator was executed, the more inaccurate it became. Thus, the performance of controllers with internal simulators reduced over time unless their internal simulator was periodically corrected.

中文翻译：

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基于神经网络的模拟器促进具有本体感觉的进化机器人控制器

本研究从人类的导航能力中汲取灵感，研究了一种为机器人控制器提供基本位置感的方法。它将机器人模拟器整合到机器人控制器中，为他们提供一种机制来近似他们的行为对机器人的影响。测试和比较了带有和不带有内部模拟器的控制器。所提出的控制器架构被证明优于常规控制器架构。然而，内部模拟器执行的时间越长，它就越不准确。因此，除非定期校正内部模拟器，否则带有内部模拟器的控制器的性能会随着时间的推移而降低。