Spatio-temporal representation for long-term anticipation of human presence in service robotics

Vintr, Tomas and Yan, Zhi and Duckett, Tom and Krajnik, Tomas (2019) Spatio-temporal representation for long-term anticipation of human presence in service robotics. In: 2019 International Conference on Robotics and Automation (ICRA), 20-24 May 2019, Montreal, Canada.

Full content URL: http://doi.org/10.1109/ICRA.2019.8793534

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Spatio-temporal representation for long-term anticipation of human presence in service robotics
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Item Type:Conference or Workshop contribution (Paper)
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Abstract

We propose an efficient spatio-temporal model for mobile autonomous robots operating in human populated
environments. Our method aims to model periodic temporal patterns of people presence, which are based on peoples’
routines and habits. The core idea is to project the time onto a set of wrapped dimensions that represent the periodicities of people presence. Extending a 2D spatial model with this multi-dimensional representation of time results in a memory efficient spatio-temporal model. This model is capable of long-term predictions of human presence, allowing mobile robots to schedule their services better and to plan their paths. The experimental evaluation, performed over datasets gathered by a robot over a period of several weeks, indicates that the proposed
method achieves more accurate predictions than the previous state of the art used in robotics.

Keywords:long-term autonomy, autonomous mobile robots, human activity monitoring
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Computer Science
ID Code:38253
Deposited On:06 Nov 2019 09:30

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