SPNets: Human-like Navigation Behaviors with Uncertain Goals

SPNets: Human-like Navigation Behaviors with Uncertain Goals
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SPNet:目标不确定的类人导航行为

DOI:
10.1145/3424636.3426911
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发表时间:
2020
期刊:
SPNets: Human-like Navigation Behaviors with Uncertain Goals
影响因子:
--
通讯作者:
Guy, Stephen J.
Guy, Stephen J.
中科院分区:
--
文献类型:
--
作者:
Sohre, Nicholas;Guy, Stephen J.

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大多数路径规划技术使用准确的、全局的环境信息来制定最优或接近最优的计划。相比之下,人类只使用当地信息导航,他们必须通过对典型建筑布局的理解来增强这些信息,以猜测前方是什么,同时整合他们已经看到的东西,形成对建筑结构的心理表征。在这里,我们提出了场景规划网络(SPNets),这是一种基于神经网络的方法,用于将远程导航问题描述为一系列类似于人类导航时所面临的局部决策。使用SPNet导航的代理建立先前观测的附加神经表示来理解局部障碍结构,并使用基于网络的规划方法来规划通往模糊目标区域的下一步。我们的方法再现了人类行为的几个重要方面,这些方面既不是完全的全球规划,也不是简单的局部启发式。
Most path planning techniques use exact, global information of the environment to make optimal or near-optimal plans. In contrast, humans navigate using only local information, which they must augment with their understanding of typical building layouts to guess what lies ahead, while integrating what they have seen already to form mental representations of building structure. Here, we propose Scene Planning Networks (SPNets), a neural network based approach for formulating the long-range navigation problem as a series of local decisions similar to what humans face when navigating. Agents navigating using SPNets build additive neural representations of previous observations to understand local obstacle structure, and use a network-based planning approach to plan the next steps towards a fuzzy goal region. Our approach reproduces several important aspects of human behavior that are not captured by either full global planning or simple local heuristics.
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