The vehicle kinematics model based on Ackerman principle has a wide range of applications in the field of unmanned driving, and the motion planning control of autonomous mobile intelligent vehicles is of great significance for the research of unmanned driving. In this paper, the robot operating system (ROS) is used as the development platform to establish the simulation model of Ackerman intelligent vehicle, and the three-dimensional physical simulation software Gazebo is used to build the simulation environment. The improved rapid expansion random tree (RRT) algorithm is used as the global path planning algorithm, and the TEB algorithm is used for local path planning to complete the simulation verification of the motion planning and control of the Ackerman smart car. The simulation results show that the improved RRT algorithm can obtain the optimal global path, and its search efficiency and path smoothness are significantly improved. Ackerman intelligent vehicle uses this algorithm to move autonomously in the 3D physical simulation environment, and can avoid obstacles in real time, presenting a good simulation effect.


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    Title :

    Simulation of motion planning control of Ackerman intelligent vehicle based on ROS


    Contributors:

    Conference:

    Third International Conference on Mechanical Design and Simulation (MDS 2023) ; 2023 ; Xi'an, China


    Published in:

    Proc. SPIE ; 12639


    Publication date :

    2023-06-16





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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