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首页> 外文期刊>Journal of terramechanics >Evaluating mobility vs. latency in unmanned ground vehicles
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Evaluating mobility vs. latency in unmanned ground vehicles

机译：评估无人地面车辆的机动性与时延

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As the penetration levels of unmanned ground vehicles (UGVs) in military applications increase, there is a growing need to evaluate their mobility across different latencies and various modes of operation ranging from pure teleoperation to full autonomy. State-of-the-art tools to evaluate mobility of ground vehicles do not address this need due to their not accounting for UGV technologies and the associated latencies. Although the trade-off between latency and performance has been thoroughly studied in the telerobotics literature and the results may qualitatively shed light onto the UGV domain, as well, a quantitative generalization is not possible due to the differences in context. Recognizing this gap, this paper presents a functional relationship between mobility and latency in high-speed, teleoperated UGVs under the context of path following. Specifically, data from human-in-the-loop simulations performed in this paper are combined with data from prior studies to span three vehicle types, three courses, and teleoperation latencies ranging from 0 s to 1 s. This combination yields for the first time a diverse data set for the context of path following in high speed, teleoperated UGVs. Based on this data set, empirical relationships are derived to quantify the trade-off between latency versus average speed and lane keeping error. These relationships can be used to establish a benchmark to evaluate the performance of autonomy-enabled UGV systems. (C) 2018 ISTVS. Published by Elsevier Ltd. All rights reserved.
机译：随着无人地面车辆（UGV）在军事应用中的渗透水平的提高，人们越来越需要评估其在不同时延和各种操作模式（从纯远程操作到完全自治）之间的机动性。评估地面车辆机动性的最新工具无法满足这一需求，因为它们没有考虑到UGV技术和相关的延迟。尽管在远程机器人文献中已经充分研究了延迟和性能之间的折衷，并且其结果也可能从质量上阐明了UGV域，但由于上下文的不同，无法进行定量概括。认识到这一差距，本文提出了在路径跟随的背景下，高速，远程操作的UGV中的移动性与等待时间之间的功能关系。具体而言，将本文中进行的“在车模拟”数据与以前的研究数据相结合，以涵盖三种车辆类型，三种航向以及从0 s到1 s的远程操作等待时间。这种结合首次为高速遥控UGV中的路径跟踪提供了多样化的数据集。基于该数据集，得出经验关系以量化等待时间与平均速度和车道保持误差之间的权衡。这些关系可用于建立基准，以评估支持自治的UGV系统的性能。 （C）2018年ISTVS。由Elsevier Ltd.出版。保留所有权利。

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