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Authors: Timo Korthals ; Marvin Barther ; Thomas Schöpping ; Stefan Herbrechtsmeier and Ulrich Rückert

Affiliation: Bielefeld University, Germany

Keyword(s): Occupancy Grid Mapping, Inverse Sensor Model, Inverse Particle Filter, Uncertain Range Sensors.

Related Ontology Subjects/Areas/Topics: Adaptive Signal Processing and Control ; Informatics in Control, Automation and Robotics ; Mobile Robots and Autonomous Systems ; Perception and Awareness ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: A huge number of techniques for detecting and mapping obstacles based on LIDAR and SONAR exist, though not taking approximative sensors with high levels of uncertainty into consideration. The proposed mapping method in this article is undertaken by detecting surfaces and approximating objects by distance using sensors with high localization ambiguity. Detection is based on an Inverse Particle Filter, which uses readings from single or multiple sensors as well as a robot’s motion. This contribution describes the extension of the Sequential Importance Resampling filter to detect objects based on an analytical sensor model and embedding into Occupancy Grid Maps. The approach has been applied to the autonomous mini robot AMiRo in a distributed way. There were promising results for its low-power, low-cost proximity sensors in various real life mapping scenarios, which outperform the standard Inverse Sensor Model approach.

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Paper citation in several formats:
Korthals, T.; Barther, M.; Schöpping, T.; Herbrechtsmeier, S. and Rückert, U. (2016). Occupancy Grid Mapping with Highly Uncertain Range Sensors based on Inverse Particle Filters. In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-198-4; ISSN 2184-2809, SciTePress, pages 192-200. DOI: 10.5220/0005960001920200

@conference{icinco16,
author={Timo Korthals. and Marvin Barther. and Thomas Schöpping. and Stefan Herbrechtsmeier. and Ulrich Rückert.},
title={Occupancy Grid Mapping with Highly Uncertain Range Sensors based on Inverse Particle Filters},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2016},
pages={192-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005960001920200},
isbn={978-989-758-198-4},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Occupancy Grid Mapping with Highly Uncertain Range Sensors based on Inverse Particle Filters
SN - 978-989-758-198-4
IS - 2184-2809
AU - Korthals, T.
AU - Barther, M.
AU - Schöpping, T.
AU - Herbrechtsmeier, S.
AU - Rückert, U.
PY - 2016
SP - 192
EP - 200
DO - 10.5220/0005960001920200
PB - SciTePress