University of Oulu

R. Raveendran, S. Ariram, A. Tikanmäki and J. Röning, "Development of task-oriented ROS-based Autonomous UGV with 3D Object Detection," 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR), Asahikawa, Japan, 2020, pp. 427-432, doi: 10.1109/RCAR49640.2020.9303034

Development of task-oriented ROS-based autonomous UGV with 3D object detection

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Author: Raveendran, Rajesh1; Ariram, Siva1; Tikanmäki, Antti1;
Organizations: 1Biomimetics and Intelligent Systems Group(BISG), University of Oulu, 90570 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2021-02-15


In a scenario where fire accidents takes place the priority is always human safety and acting swiftly to contain the fire from further spreading. The modern autonomous systems can promise both human safety and can perform actions rapidly. One such scenario which is motivated by urban firefighting was designed in challenge 3 of MBZIRC 2020 competition. In this challenge the UAV’s and UGV collaborate autonomously to detect the fire and quench the flames with water. So, in this project we have developed Robot Operating System (ROS)-based autonomous system to solve the challenge for UGV criteria by detecting targeted objects in real-time, in our case its simulated fire and red colored softballs. Then finally localize those targets as markers in the map and navigate autonomously to all those targets. This work has two sections, in the first section mapping and localizing the fire and softballs in highly cluttered environment and then reaching those targets autonomously. Robustly mapping the area with adequate sensors and detection of targets with optimally trained CNN based network is the key to localizing of the targeted objects in a highly cluttered environments.

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ISBN: 978-1-7281-7293-4
ISBN Print: 978-1-7281-7294-1
Pages: 427 - 432
DOI: 10.1109/RCAR49640.2020.9303034
Host publication: 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Conference: IEEE International Conference on Real-Time Computing and Robotics
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: We wish to thank University of Oulu which allowed us to collect the FSB Data-set in their warehouse. Our special thanks to Marko Kauppinen who helped with the data-set collection and providing technical support for M¨orri.
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