本教程将详细介绍如何在Jetson Orin Nano上安装Ubuntu 22.04和ROS2,并集成宇树L2激光雷达与Fast-LIO2算法,最终实现PX4飞控的定点模式。适合初学者和小白用户。
你需要以下硬件:
在Jetson Orin Nano上刷写Ubuntu 22.04系统。推荐使用NVIDIA SDK Manager或直接烧录官方镜像。确保系统更新:
sudo apt update && sudo apt upgrade -y
ROS2是机器人操作系统,用于节点间通信。按照官方文档安装ROS2 Humble:
sudo apt install software-properties-commonsudo add-apt-repository universesudo apt update && sudo apt install curl -ysudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpgecho "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(. /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/nullsudo apt updatesudo apt install ros-humble-desktop python3-colcon-common-extensions
设置环境变量:
echo "source /opt/ros/humble/setup.bash" >> ~/.bashrcsource ~/.bashrc
宇树L2激光雷达是高性能激光雷达,需要安装驱动。从宇树官方GitHub克隆驱动包:
mkdir -p ~/ros2_ws/srccd ~/ros2_ws/srcgit clone https://github.com/unitreerobotics/L2_lidar_driver_ros2.git
编译:
cd ~/ros2_wscolcon build --packages-select l2_lidar_driversource install/setup.bash
连接激光雷达,启动驱动节点:
ros2 launch l2_lidar_driver l2_lidar_launch.py
Fast-LIO2是高效激光雷达惯性里程计算法,可实现高精度定位。克隆代码:
cd ~/ros2_ws/srcgit clone https://github.com/Livox-SDK/livox_ros_driver2.gitgit clone https://github.com/zlwang7/Fast_LIO2.git
注意:宇树L2兼容Livox协议,可直接使用livox_ros_driver2。编译:
cd ~/ros2_wscolcon build --packages-select livox_ros_driver2colcon build --packages-select fast_lio2source install/setup.bash
配置Fast-LIO2参数文件,修改激光雷达类型为Livox系列,话题名称与宇树L2驱动发布的话题一致(通常是/pointcloud)。
PX4是一款开源飞控,支持定点模式。首先在Jetson Orin Nano上安装MAVROS或MAVSDK,用于与飞控通信。使用MAVROS:
sudo apt install ros-humble-mavros ros-humble-mavros-extrassudo geographiclib-get-geoids egm2008-1
将飞控通过USB连接到Jetson,启动MAVROS节点:
ros2 launch mavros px4.launch.py fcu_url:=/dev/ttyACM0:921600
注意:根据实际串口设备修改fcu_url。
定点模式需要位置信息。Fast-LIO2输出里程计数据(/Odometry),我们需要将其转换为飞控可用的位置设定点。可以编写一个ROS2节点订阅Fast-LIO2的odometry,并通过MAVROS的/setpoint_position/local话题发送给飞控。此处提供一个简单示例:
import rclpyfrom rclpy.node import Nodefrom nav_msgs.msg import Odometryfrom geometry_msgs.msg import PoseStampedclass PositionSetpoint(Node): def init(self): super().init("position_setpoint") self.sub = self.create_subscription(Odometry, "/Odometry", self.odom_callback, 10) self.pub = self.create_publisher(PoseStamped, "/mavros/setpoint_position/local", 10) def odom_callback(self, msg): pose = PoseStamped() pose.header = msg.header pose.pose = msg.pose.pose self.pub.publish(pose)def main(args=None): rclpy.init(args=args) node = PositionSetpoint() rclpy.spin(node) node.destroy_node() rclpy.shutdown() 编译该节点,运行。然后在QGC地面站中设置飞行模式为"定点"或通过ROS2服务切换。
启动激光雷达驱动、Fast-LIO2、MAVROS和位置设定点节点。在QGC中查看无人机位置估计是否准确,尝试切换定点模式,无人机应能悬停或按指令移动。
通过以上步骤,你就在Jetson Orin Nano上实现了基于宇树L2激光雷达和Fast-LIO2的PX4定点模式。本教程中使用的Jetson Orin Nano、宇树L2激光雷达、Fast-LIO2算法和PX4定点模式是关键要素。
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