Sergi Molina, Grzegorz Cielniak, Tomás Krajník, and Tom Duckett
Modelling and Predicting Rhythmic Flow Patterns in Dynamic Environments
2018 Conference Towards Autonomous Robotic Systems (TAROS)
Abstract
In this paper we present a time-dependent probabilistic map able to model and predict flow patterns of people in indoor environments. The proposed representation models the likelihood of motion direction on a grid-based map by a set of harmonic functions, which efficiently capture long-term (minutes to weeks) variations of crowd movements over time. The evaluation, performed on data from two real environments, shows that the proposed model enables prediction of human movement patterns in the future. Potential applications include human-aware motion planning, improving the efficiency and safety of robot navigation.
@incollection{Molina2018,
doi = {10.1007/978-3-319-96728-8_12},
url = {https://doi.org/10.1007/978-3-319-96728-8_12},
year = {2018},
publisher = {Springer International Publishing},
pages = {135--146},
author = {Sergi Molina and Grzegorz Cielniak and Tom{\'{a}}{\v{s}} Krajn{\'{\i}}k and Tom Duckett},
title = {Modelling and Predicting Rhythmic Flow Patterns in Dynamic Environments},
booktitle = {Towards Autonomous Robotic Systems}
}