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From skylight input to behavioural output: A computational model of the insect polarised light compass

机译:从天窗输入到行为输出:昆虫偏光灯指示灯的计算模型

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摘要

Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to 'true north' during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.
机译:许多昆虫通过集成在向外路径上行进的距离和方向而导航,允许直接返回起点。这个过程的可靠性的基础是基于外部天线的主要指南针使用。在这里,考虑到天空偏振图案和昆虫眼睛传感器阵列的现实约束,我们如何检查这些指南针信息如何可靠地计算这些指南针信息。通过处理不同方向的不同方向的极化程度,我们的模型可以直接估计太阳能方位角并推断估计的置信度。我们介绍一种纠正传感器阵列的倾斜的方法,可能是由不均匀地形的旅行引起的。我们还表明,信心可用于接近太阳位置随着时间的推移的变化,允许指南针在长途徒步旅行期间仍然相对于“真正的北”来固定。我们证明指南针对扰动具有鲁棒性,并且可以有效地用作对昆虫路径集成的现有神经模型的输入。我们讨论了我们模型的合理性映射到已知的神经电路,并为机器人导航实施。

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