Spatio-temporal representation for long-term anticipation of human presence in service robotics
Spatio-temporal representation for long-term anticipation of human presence in service robotics
复制标题
服务机器人中人类存在的长期预期的时空表示
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
T. Krajník
中科院分区：
文献类型：
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作者：
Tomáš Vintr;Zhi Yan;T. Duckett;T. Krajník
我们提出了一个有效的时空模型移动的自主机器人在人类居住的环境中运行。我们的方法旨在对人们存在的周期性时间模式进行建模，这些模式基于人们的日常生活和习惯。其核心思想是将时间投射到一组包装的维度上，这些维度代表人们存在的周期性。用时间的这种多维表示扩展2D空间模型会导致存储器高效的时空模型。该模型能够长期预测人类的存在，使移动的机器人更好地安排他们的服务，并规划他们的路径。对机器人在几周内收集的数据集进行的实验评估表明，所提出的方法比机器人技术中使用的现有技术实现了更准确的预测。
We propose an efficient spatio-temporal model for mobile autonomous robots operating in human populated environments. Our method aims to model periodic temporal patterns of people presence, which are based on peoples’ routines and habits. The core idea is to project the time onto a set of wrapped dimensions that represent the periodicities of people presence. Extending a 2D spatial model with this multidimensional representation of time results in a memory efficient spatio-temporal model. This model is capable of long-term predictions of human presence, allowing mobile robots to schedule their services better and to plan their paths. The experimental evaluation, performed over datasets gathered by a robot over a period of several weeks, indicates that the proposed method achieves more accurate predictions than the previous state of the art used in robotics.