2019
DOI: 10.1109/lra.2019.2926682
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Warped Hypertime Representations for Long-Term Autonomy of Mobile Robots

Abstract: This paper presents a novel method for introducing time into discrete and continuous spatial representations used in mobile robotics, by modelling long-term, pseudoperiodic variations caused by human activities. Unlike previous approaches, the proposed method does not treat time and space separately, and its continuous nature respects both the temporal and spatial continuity of the modeled phenomena. The method extends the given spatial model with a set of wrapped dimensions that represent the periodicities of… Show more

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Cited by 24 publications
(20 citation statements)
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“…This is caused by the fact that the modeled events are sparse, and the process generating them is not stationary. To deal with the problem, we proposed in our previous works to we use a "warped-hypertime" projection of the time line into a closed subset of multidimensional vector space, where each pair of dimensions would represent one periodicity [38], [39], [40], [41], [42]. Then, we create a model characterising the probability distribution of spatiodirection-temporal events in the vector space extended by the warped hypertime.…”
Section: Methods Descriptionmentioning
confidence: 99%
See 2 more Smart Citations
“…This is caused by the fact that the modeled events are sparse, and the process generating them is not stationary. To deal with the problem, we proposed in our previous works to we use a "warped-hypertime" projection of the time line into a closed subset of multidimensional vector space, where each pair of dimensions would represent one periodicity [38], [39], [40], [41], [42]. Then, we create a model characterising the probability distribution of spatiodirection-temporal events in the vector space extended by the warped hypertime.…”
Section: Methods Descriptionmentioning
confidence: 99%
“…where n is the number of positions, k is the number of angular bins for the direction of people motion in the cells C. Methods compared in the experiment 1) WHyTe: There are two parameters, which affect the quality of WHyTe -the number of clusters c and the set of periodicities. The recent experiments showed, that the number of clusters could be relatively small (usually up to 9) [42], and it seems, that the number of clusters is in relation with the topological structure of the space [41]. For this dataset from T-junction we chose c = 3 clusters.…”
Section: B Evaluation Methodologymentioning
confidence: 99%
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“…point cloud) about its environment over a long range and wide angle. Moreover, it is robust to lightness variance, thereby very suitable for long-term robot autonomy (Krajník et al, 2019;Vintr et al, 2019;Kunze et al, 2018). However, due to the low feature density compared to cameras, false positives are more likely.…”
Section: Human Detection and Trackingmentioning
confidence: 99%
“…In the following sections, we will refer to these models as 'symbolic' and 'metric', respectively. The aforementioned datasets are available as a part of the longterm dataset collection [44].…”
Section: Dataset Summarymentioning
confidence: 99%