Time-varying pedestrian flow models for service robots

Tomas Vintr, Sergi Molina, Ransalu Senanayake, George Broughton, Zhi Yan, Jiri Ulrich, Tomasz Piotr Kucner, Chittaranjan Srinivas Swaminathan, Filip Majer, Maria Stachova, Achim J. Lilienthal, Tomas Krajnik

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

7 Citations (Scopus)


We present a human-centric spatiotemporal model for service robots operating in densely populated environments for long time periods. The method integrates observations of pedestrians performed by a mobile robot at different locations and times into a memory efficient model, that represents the spatial layout of natural pedestrian flows and how they change over time. To represent temporal variations of the observed flows, our method does not model the time in a linear fashion, but by several dimensions wrapped into themselves. This representation of time can capture long-term (i.e. days to weeks) periodic patterns of peoples' routines and habits. Knowledge of these patterns allows making long-term predictions of future human presence and walking directions, which can support mobile robot navigation in human-populated environments. Using datasets gathered for several weeks, we compare the model to state-of-the-art methods for pedestrian flow modelling.
Original languageEnglish
Title of host publicationProceedings of European Conference on Mobile Robots, ECMR 2019
Number of pages7
ISBN (Electronic)9781728136059
Publication statusPublished - Sep 2019
MoE publication typeA4 Article in a conference publication
EventEuropean Conference on Mobile Robots - Prague, Czech Republic
Duration: 4 Sep 20196 Sep 2019
Conference number: 11


ConferenceEuropean Conference on Mobile Robots
Abbreviated titleECMR
Country/TerritoryCzech Republic
Internet address


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