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Autonomous spacecraft landing through human pre-attentive vision

机译:通过人类注意力集中的自主航天器降落

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摘要

In this work, we exploit a computational model of human pre-attentive vision to guide the descent of a spacecraft on extraterrestrial bodies. Providing the spacecraft with high degrees of autonomy is a challenge for future space missions. Up to present, major effort in this research field has been concentrated in hazard avoidance algorithms and landmark detection, often by reference to a priori maps, ranked by scientists according to specific scientific criteria. Here, we present a bio-inspired approach based on the human ability to quickly select intrinsically salient targets in the visual scene; this ability is fundamental for fast decision-making processes in unpredictable and unknown circumstances. The proposed system integrates a simple model of the spacecraft and optimality principles which guarantee minimum fuel consumption during the landing procedure; detected salient sites are used for retargeting the spacecraft trajectory, under safety and reachability conditions. We compare the decisions taken by the proposed algorithm with that of a number of human subjects tested under the same conditions. Our results show how the developed algorithm is indistinguishable from the human subjects with respect to areas, occurrence and timing of the retargeting.
机译:在这项工作中,我们利用人类注意力集中的视觉计算模型来指导航天器在地外物体上的下降。为航天器提供高度自治是未来航天任务的挑战。到目前为止,该研究领域的主要工作一直集中在危险规避算法和地标检测上,通常是参考先验图,由科学家根据特定的科学标准对其进行排名。在这里,我们提出一种基于生物的方法,该方法基于人类快速选择视觉场景中内在突出目标的能力。在无法预测和未知的情况下,此功能对于快速决策过程至关重要。拟议的系统集成了航天器的简单模型和最优原理,可确保降落过程中的最低油耗;在安全性和可达性条件下,将检测到的显着位置用于重新确定航天器的轨迹。我们将所提出算法的决策与在相同条件下测试的许多人类受试者的决策进行比较。我们的结果表明,在重新定位的区域,发生和时间方面,开发的算法与人类对象之间是无法区分的。

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