Development of ROS-based Small Unmanned Platform for Acquiring Autonomous Driving Dataset in Various Places and Weather Conditions

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As autonomous driving research has actively pro-gressed, software for autonomous vehicles and embedded systems such as Apollo and AutoWare have also been developed, providing a complete set of self-driving modules, including perception, localization and mapping, path planning, prediction, decision making, and control. Most of the researchers currently use these software programs, but many researchers have also studied autonomous driving based on the middleware software termed robot operating system (ROS) before such software was released, especially in academia. Accordingly, we intend to develop ROS-based unmanned RC car equipped with autonomous driving sensors such as LiDAR, radar, VIS/IR cameras, GPS, and IMUs that can provide ROS-based datasets to researchers studying self-driving cars and robots using ROS. In addition, unlike conventional datasets, we acquire dataset not only on road but also pedestrian paths that can be used in both vehicles and robots and provides extreme environmental datasets such as snowfall environments. In this sense, the ROS dataset we created will be helpful to researchers studying autonomous vehicles and robots by using ROS.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Issue Date
2022-07
Language
English
Citation

46th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2022, pp.24 - 31

DOI
10.1109/COMPSAC54236.2022.00013
URI
http://hdl.handle.net/10203/299049
Appears in Collection
ME-Conference Papers(학술회의논문)
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