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Conference papers

Lane Detection and Trajectory Generation System

Abstract : This paper presents the development of a perception system that enables an Ackermann-type autonomous vehicle to move through urban environments using control commands based on short-term trajectory planning. We propose a lane detection and keeping system based on computer vision techniques that are computationally efficient. Also, a Kalman filter-based estimation module was added to gain robustness against illumination changes and shadows. Additionally, the simulation and control of the Autónomo Uno robot gave good results following the steering commands to keep the position. In the simulation the controllers had some slight noise problems but the robot executed the given steering commands and it moved following the road. This behavior was also seen in the physical implementation.
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Conference papers
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Contributor : Manuel Diaz Zapata Connect in order to contact the contributor
Submitted on : Friday, December 4, 2020 - 11:04:24 PM
Last modification on : Wednesday, November 3, 2021 - 3:58:53 AM


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  • HAL Id : hal-03041445, version 1



Manuel Alejandro Diaz-Zapata, Jose Correa-Sandoval, Juan Perafán-Villota, Víctor Romero- Cano. Lane Detection and Trajectory Generation System. LACAR 2019 - Latin American Conference on Automation and Robotics, Oct 2019, Cali, Colombia. ⟨hal-03041445⟩



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