该研究设计了一款基于机器人操作系统(Robot Operating System，ROS)和同步定位与建图(Simultaneous Localization and Mapping，SLAM)技术的无人车。采用 STM32F407 为底层驱动，树莓派为控制核心。基于无人车运动学模型，采用激光雷达和MPU9250姿态传感器，解算无人车的位姿，使用自适应蒙特卡罗算法进行定位、构建实时地图。使用Astra Pro深度RGBD相机，通过OpenCV图像处理技术进行巡线、颜色跟踪、物体识别。通过A*算法进行路径规划并对算法优化，提高无人车避障和路径搜索能力。实验结果表明该无人车鲁棒性良好，又具有成本低、功能可拓展等特点。
Design and implementation of unmanned vehicle control system based on ROS
This study designed an unmanned vehicle based on Robot Operating System(ROS)and Simulta-neous Localization and Mapping(SLAM)technology.STM32F407 is used as the bottom drive and Rasp-berry Pi as the control core.Based on the kinematics model of the unmanned vehicle,the laser radar and MPU9250 attitude sensor are used to calculate the position and attitude of the unmanned vehicle,and the a-daptive Monte Carlo algorithm is used to locate and build a real-time map.The Astra Pro depth RGBD camera is used for line patrol,color tracking and object recognition through OpenCV image processing tech-nology.A*algorithm is used for path planning and optimization to improve the obstacle avoidance and path search capabilities of unmanned vehicles.The experiment results show that the unmanned vehicle has good robustness,low cost and expandable functions.
Raspberry Piunmanned vehicleSimultaneous Locatization and Mappingpath planningau-tonomous navigation
万方数据
维普
