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Authors: Felix Becker and Marc Ebner

Affiliation: Ernst Moritz Arndt Universität Greifswald, Institut für Mathematik und Informatik, Walther-Rathenau-Str. 47, 17487 Greifswald and Germany

Keyword(s): Collision Detection, Autonomous Mobile Robots, Acceleration Sensor.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Mobile Robots and Autonomous Systems ; Robotics and Automation

Abstract: Collisions cannot be entirely avoided during normal operation of an autonomous mobile robot. Therefore, mobile robots need to detect collisions and react appropriately when they happen. We investigate whether logistic regression on acceleration data can be used for collision detection. We have collected training data from an acceleration sensor during normal driving behavior of a small mobile robot. Collisions were manually marked by a human operator. Accelerations occurring in a direction opposite to the current direction of motion are more likely to be actual collisions. Hence, we combine accelerometer data and motor commands in the logistic regression model. The trained model was able to detect 13 out of 14 collisions on a separate test set with no false positives.

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Paper citation in several formats:
Becker, F. and Ebner, M. (2019). Collision Detection for a Mobile Robot using Logistic Regression. In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-380-3; ISSN 2184-2809, SciTePress, pages 167-173. DOI: 10.5220/0007768601670173

@conference{icinco19,
author={Felix Becker. and Marc Ebner.},
title={Collision Detection for a Mobile Robot using Logistic Regression},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2019},
pages={167-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007768601670173},
isbn={978-989-758-380-3},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Collision Detection for a Mobile Robot using Logistic Regression
SN - 978-989-758-380-3
IS - 2184-2809
AU - Becker, F.
AU - Ebner, M.
PY - 2019
SP - 167
EP - 173
DO - 10.5220/0007768601670173
PB - SciTePress

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