A set of depth sensor processing ROS tools for wheeled mobile robot navigation

• Autorzy: Drwięga M. , Jakubiak J.

Identyfikatory

DOI

10.14313/JAMRIS_2-2017/16

• Języki publikacji: EN

Abstrakty

EN

The paper presents a set of soŌware tools dedicated to support mobile robot navigaƟon. The tools are used to process an image from a depth sensor. They are implemented in ROS framework and they are compaƟble with standard ROS navigaƟon packages. The soŌware is released with an open source licence. First of the tools converts a 3D depth image to a 2D scan in polar coordinates. It provides projecƟon of the obstacles, removes the ground plane from the image and compensates sensor Ɵlt angle. The node is faster than the standard node within ROS and it has addiƟonal funcƟons increasing range of possible applicaƟons. The second tool allows detecƟon of negaƟve obstacles i.e. located below the ground plane level. The third tool esƟmates height and orientaƟon of the sensor with RANSAC algorithm applied to the depth image. The paper presents also the results of usage of the tools with mobile plaƞorms equipped with MicrosoŌ Kinect sensors. The plaƞorms are elements of the ReMeDi project within which the soŌware was developed.

Słowa kluczowe

EN

RGB-D; Kinect; mobile robot; ROS; depth sensor; navigation tools

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2017
• Tom: Vol. 11, No. 2
• Strony: 48--56
• Opis fizyczny: Bibliogr. 35 poz., rys.

Twórcy

autor

Drwięga M.

• Department of Cybernetics and Robotics, Faculty of Electronics, Wrocław University of Technology, ul. Wybrzeże Wyspiań skiego 27, 50-370 Wrocław, Poland

autor

Jakubiak J.

• Department of Cybernetics and Robotics, Faculty of Electronics,Wrocław University of Technology, ul. Wybrzeże Wyspiań skiego 27, 50-370 Wrocław, Poland

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).