Go with the Flow: Exploration and Mapping of Pedestrian Flow Patterns from Partial Observations

Molina, Sergi and Cielniak, Grzegorz and Duckett, Tom (2019) Go with the Flow: Exploration and Mapping of Pedestrian Flow Patterns from Partial Observations. In: International Conference on Robotics and Automation (ICRA).

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Go with the Flow: Exploration and Mapping of Pedestrian Flow Patterns from Partial Observations
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Abstract

Understanding how people are likely to behave in an environment is a key requirement for efficient and safe robot navigation. However, mobile platforms are subject to spatial and temporal constraints, meaning that only partial observations of human activities are typically available to a robot, while the activity patterns of people in a given environment may also change at different times. To address these issues we present as the main contribution an exploration strategy for acquiring models of pedestrian flows, which decides not only the locations to explore but also the times when to explore them. The approach is driven by the uncertainty from multiple Poisson processes built from past observations. The approach is evaluated using two long-term pedestrian datasets, comparing its performance against uninformed exploration strategies. The results show that when using the uncertainty in the exploration policy, model accuracy increases, enabling faster learning of human motion patterns.

Keywords:Mobile Robots, mobile robot exploration, long-term data
Subjects:H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
ID Code:36396
Deposited On:18 Jul 2019 08:46

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