Time-varying Pedestrian Flow Models for Service Robots
| Autor: | Filip Majer, George Broughton, Sergi Molina, Achim J. Lilienthal, Maria Stachova, Jiri Ulrich, Tomasz Piotr Kucner, Tomas Vintr, Ransalu Senanayake, Chittaranjan Srinivas Swaminathan, Zhi Yan, Tomas Krajnik |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Service (systems architecture) Computer science Computer Sciences Real-time computing Human Motion Prediction Mobile robot 02 engineering and technology Pedestrian Mobile robot navigation 020901 industrial engineering & automation Spatio-Temporal Models Datavetenskap (datalogi) 0202 electrical engineering electronic engineering information engineering Trajectory Robot Long-Term Operation 020201 artificial intelligence & image processing Flow Models Representation (mathematics) Hidden Markov model |
| Zdroj: | ECMR |
| Popis: | 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. Funding Agencies:CSF project 17-27006Y STRoLLCTU IGA grant SGS16/235/OHK3/3T/13 FR-8J18FR018PHC Barrande programme 40682ZH (3L4AV)CZ grant CZ.02.1.01/0.0/0.0/16 019/0000765 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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