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Time-varying Pedestrian Flow Models for Service Robots
Artificial Intelligence Center, Czech Technical University.
Lincoln Centre for Autonomous Systems (L-CAS), University of Lincoln.
Stanford University.
Artificial Intelligence Center, Czech Technical University.
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2019 (English)In: 2019 European Conference on Mobile Robots (ECMR), IEEE, 2019, article id 8870909Conference paper, Published paper (Refereed)
Abstract [en]

We present a human-centric spatio-temporal 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 by a robot for several weeks, we compare the model to state-of-the-art methods for pedestrian flow modelling.

Place, publisher, year, edition, pages
IEEE, 2019. article id 8870909
Keywords [en]
Long-Term Operation, Flow Models, Spatio-Temporal Models, Human Motion Prediction
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-79740DOI: 10.1109/ECMR.2019.8870909Scopus ID: 2-s2.0-85074395312ISBN: 978-1-7281-3605-9 (electronic)OAI: oai:DiVA.org:oru-79740DiVA, id: diva2:1391186
Conference
European Conference on Mobile Robotics (ECMR), Prague, Czech Republic, September 4 - 6, 2019
Funder
EU, Horizon 2020, 732737Available from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-14Bibliographically approved

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Time-varying Pedestrian Flow Models for Service Robots(744 kB)35 downloads
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