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Path Planning and Following for an Autonomous Model Car Using an “Eye in the Sky”

Rodrigo Rill-García*, Jose Martinez-Carranza, Edgar Granados, Marco Morales

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapter in a book

    1 Citation (Scopus)

    Abstract

    Autonomous driving is a trend topic that is enabled by communication between devices. Under this scope, ROS is a useful tool for running multiple processes in a graph architecture, where each node may receive and post messages that are consumed by other nodes for their own needs. In this tutorial chapter we discuss a solution for autonomous path planning using a Randomized Random Tree (RRT) and a simple control scheme based on PIDs to follow that path. The control uses internal sensors and an external camera that works as an “eye in the sky”. This is implemented with the help of ROS version 1.12.13 using the Kinetic distribution. Results are validated using the Gazebo multi-robot simulator, version 7.0.0. The robot model used corresponds to the AutoNOMOS mini developed by PHD Raúl Rojas, while the “eye in the sky” is an artificial simple RGB camera created in Gazebo for research purposes. The Rviz package is used to monitor the simulation. The repository for this project can be found at https://github.com/Sutadasuto/AutoNOMOS_Stardust. (The original model for the AutoNOMOS mini was retrieved from https://github.com/EagleKnights/EK_AutoNOMOS_Sim ).

    Original languageEnglish
    Title of host publicationRobot Operating System (ROS)
    Subtitle of host publicationThe Complete Reference
    EditorsAnis Koubaa
    PublisherSpringer Verlag
    Pages25-51
    Number of pages27
    Volume4
    ISBN (Electronic)978-3-030-20190-6
    ISBN (Print)978-3-030-20189-0
    DOIs
    Publication statusE-pub ahead of print - 29 Jun 2019

    Publication series

    NameStudies in Computational Intelligence
    Volume831
    ISSN (Print)1860-949X

    Keywords

    • Autonomous driving
    • Eye in the sky
    • Path following
    • Path planning

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