Sensor Fusion Approach for an Autonomous Shunting Locomotive

  • In order to allow robust obstacle detection for autonomous freight traffic using freight trains or shunting locomotives, several different sensors are required. Humans and other objects must be detected so that the vehicle can stop in time. Laser scanners deliver distance information and are popular in robotics and automation. Cameras deliver further pieces of information on the environment and are especially useful for the classification of objects, but do not deliver distance measurements. Thermal cameras are ideal for the detection of humans based on their body temperature if the surrounding temperature is not too similar. It is only the combination of these different sensors which delivers enough robustness. Therefore a sensor fusion and an extrinsic calibration has to take place. This article presents an approach fusing a 2D and an 8-layer 3D laser scanner with a thermal and a Red-Green-Blue (RGB) camera, using a triangular calibration target taking all six degrees of freedom into account. The calibration was tested and theIn order to allow robust obstacle detection for autonomous freight traffic using freight trains or shunting locomotives, several different sensors are required. Humans and other objects must be detected so that the vehicle can stop in time. Laser scanners deliver distance information and are popular in robotics and automation. Cameras deliver further pieces of information on the environment and are especially useful for the classification of objects, but do not deliver distance measurements. Thermal cameras are ideal for the detection of humans based on their body temperature if the surrounding temperature is not too similar. It is only the combination of these different sensors which delivers enough robustness. Therefore a sensor fusion and an extrinsic calibration has to take place. This article presents an approach fusing a 2D and an 8-layer 3D laser scanner with a thermal and a Red-Green-Blue (RGB) camera, using a triangular calibration target taking all six degrees of freedom into account. The calibration was tested and the results validated during reference measurements and autonomous and manually controlled field tests. This sensor fusion approach was used for the obstacle detection of an autonomous shunting locomotive.show moreshow less

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Metadaten
Author:Johanna Gleichauf, Johannes Vollet, Christian Pfitzner, Philipp Koch, Stefan May
DOI:https://doi.org/10.1007/978-3-030-11292-9_30
ISBN:9783030112912
ISSN:1876-1100
Parent Title (English):Informatics in Control, Automation and Robotics
Subtitle (English):Conference paper
Publisher:Springer International Publishing
Place of publication:Cham
Document Type:Part of a Book
Language:English
Date of first Publication:2019/04/18
Reviewed:Begutachtet/Reviewed
Release Date:2024/07/31
Tag:Autonomous shunting locomotive; Extrinsic calibration; Object detection; Sensor fusion
Pagenumber:22
First Page:603
Last Page:624
Konferenzangabe:14th International Conference, ICINCO 2017 Madrid, Spain, July 26–28, 2017
institutes:Fakultät für Elektrotechnik Feinwerktechnik Informationstechnik
Research Themes:Digitalisierung & Künstliche Intelligenz
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