@inproceedings{5680ef146c2042dcb12ad159fb6bf498,
title = "Active speed and cruise control of the mobile robot based on the analysis of the position of the preceding vehicle",
abstract = "The aim of this study was to implement a vision system on board of a Nvidia Jetson Nano along with a camera, and to implement the Jetracer platform control. To introduce the theoretical background, literature related to image processing, active cruise control, and autonomous vehicles was reviewed. The image processing and vehicle control methods used in this paper are then described. The remainder of the paper focuses on presenting an implementation of the described algorithms. This implementation was used to conduct tests, which show that the image processing methods investigated were sufficient to control the platform. Factors affecting the quality of control have also been described, these include vehicle speed and steering control gains. Comparative time dependencies of speed and steering level were plotted for selected trials, allowing the system delays to be noted.",
keywords = "Active cruise control, Computer vision, Image segmentation, Mobile robot",
author = "Olaf Kedziora and Tomasz Grzejszczak and Eryka Probierz and Natalia Bartosiak and Martyna Wojnar and Kamil Skowronski and Adam Galuszka",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 26th International Conference on Methods and Models in Automation and Robotics, MMAR 2022 ; Conference date: 22-08-2022 Through 25-08-2022",
year = "2022",
doi = "10.1109/MMAR55195.2022.9874298",
language = "English",
series = "2022 26th International Conference on Methods and Models in Automation and Robotics, MMAR 2022 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "181--186",
booktitle = "2022 26th International Conference on Methods and Models in Automation and Robotics, MMAR 2022 - Proceedings",
address = "United States",
}