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Authors: Caio Fischer Silva 1 ; Paulo V. K. Borges 2 and José E. C. Castanho 3

Affiliations: 1 Robotics and Autonomous Systems Group, CSIRO, Australia, School of Engineering, São Paulo State University - UNESP, Bauru, SP and Brazil ; 2 Robotics and Autonomous Systems Group, CSIRO and Australia ; 3 School of Engineering, São Paulo State University - UNESP, Bauru, SP and Brazil

Keyword(s): Environment-aware Sensor Fusion using Deep Learning.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Perception and Awareness ; Robotics and Automation

Abstract: A reliable perception pipeline is crucial to the operation of a safe and efficient autonomous vehicle. Fusing information from multiple sensors has become a common practice to increase robustness, given that different types of sensors have distinct sensing characteristics. Further, sensors can present diverse performance according to the operating environment. Most systems rely on a rigid sensor fusion strategy which considers the sensors input only (e.g., signal and corresponding covariances), without incorporating the influence of the environment, which often causes poor performance in mixed scenarios. In our approach, we have adjusted the sensor fusion strategy according to a classification of the scene around the vehicle. A convolutional neural network was employed to classify the environment, and this classification is used to select the best sensor configuration accordingly. We present experiments with a full-size autonomous vehicle operating in a heterogeneous environment. The results illustrate the applicability of the method with enhanced odometry estimation when compared to a rigid sensor fusion scheme. (More)

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Paper citation in several formats:
Silva, C.; Borges, P. and Castanho, J. (2019). Environment-aware Sensor Fusion using Deep Learning. 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 88-96. DOI: 10.5220/0007841900880096

@conference{icinco19,
author={Caio Fischer Silva. and Paulo V. K. Borges. and José E. C. Castanho.},
title={Environment-aware Sensor Fusion using Deep Learning},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2019},
pages={88-96},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007841900880096},
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 - Environment-aware Sensor Fusion using Deep Learning
SN - 978-989-758-380-3
IS - 2184-2809
AU - Silva, C.
AU - Borges, P.
AU - Castanho, J.
PY - 2019
SP - 88
EP - 96
DO - 10.5220/0007841900880096
PB - SciTePress