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Binding human spatial interactions with mapping for enhanced mobility in dynamic environments

Binding human spatial interactions with mapping for enhanced mobility in dynamic environments For mobile robots to operate in compliance with human presence, interpreting the impact of human activities and responding constructively is a challenging goal. In this paper, we propose a generative approach for enhancing robot mapping and mobility in the presence of humans through a joint, probabilistic treatment of static and dynamic characteristics of indoor environments. Human spatial activity is explicitly exploited for the purpose of passage detection and space occupancy prediction while effectively discarding false positive human detections using prior map information. In turn, this allows the execution of plan trajectories within unexplored areas by using human presence for resolving the uncertainty or ambiguity that is due to dynamic events. A series of experiments with an indoor robot navigating in close human proximity within a multi-floor building demonstrate the effectiveness of our approach in realistic conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Autonomous Robots Springer Journals

Binding human spatial interactions with mapping for enhanced mobility in dynamic environments

Papadakis, Panagiotis; Rives, Patrick
Autonomous Robots , Volume 41 (5) – Jun 16, 2016
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References (37)

Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Engineering; Robotics and Automation; Artificial Intelligence (incl. Robotics); Computer Imaging, Vision, Pattern Recognition and Graphics; Control, Robotics, Mechatronics
ISSN
0929-5593
eISSN
1573-7527
DOI
10.1007/s10514-016-9581-1
Publisher site
See Article on Publisher Site

Abstract

For mobile robots to operate in compliance with human presence, interpreting the impact of human activities and responding constructively is a challenging goal. In this paper, we propose a generative approach for enhancing robot mapping and mobility in the presence of humans through a joint, probabilistic treatment of static and dynamic characteristics of indoor environments. Human spatial activity is explicitly exploited for the purpose of passage detection and space occupancy prediction while effectively discarding false positive human detections using prior map information. In turn, this allows the execution of plan trajectories within unexplored areas by using human presence for resolving the uncertainty or ambiguity that is due to dynamic events. A series of experiments with an indoor robot navigating in close human proximity within a multi-floor building demonstrate the effectiveness of our approach in realistic conditions.

Journal

Autonomous Robots – Springer Journals

Published: Jun 16, 2016

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