ubuntu20.04-ros-noetic-px4

环境配置

ubuntu20.04-ros-noetic-px4

dockerfile

在docker内配置走代理

export http_proxy=http://127.0.0.1:7890
export https_proxy=http://127.0.0.1:7890

# This is an auto generated Dockerfile for ros:ros-base
# generated from docker_images/create_ros_image.Dockerfile.em
FROM ros:noetic-ros-core-focal

# install bootstrap tools
RUN apt-get update && apt-get install --no-install-recommends -y \
    build-essential \
    python3-rosdep \
    python3-rosinstall \
    python3-vcstools \
    && rm -rf /var/lib/apt/lists/*

# bootstrap rosdep
RUN rosdep init && \
  rosdep update --rosdistro $ROS_DISTRO

# install ros packages
RUN apt-get update && apt-get install -y --no-install-recommends \
    ros-noetic-ros-base=1.5.0-1* \
    && rm -rf /var/lib/apt/lists/*

docker build -t ros:noetic .

在ARM上直接NAS拉镜像

docker load -i ~/Downloads/hilab_v2.tar

启动容器

sudo docker run -it --network host --privileged \
--gpus all \
--env="DISPLAY" \
--env="QT_X11_NO_MITSHM=1" \
--volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
ros:noetic

sudo apt-get update
sudo apt-get install vim -y

换源

PX4安装

sudo apt update
sudo apt install git -y
git clone https://github.com/PX4/PX4-Autopilot.git --recursive

bash ./PX4-Autopilot/Tools/setup/ubuntu.sh

https://github.com/PX4/PX4-Autopilot/blob/main/Tools/setup/ubuntu.sh

重启docker

sudo apt-get install protobuf-compiler libeigen3-dev libopencv-dev -y

mavros安装

sudo apt-get install ros-noetic-mavros ros-noetic-mavros-extras ros-noetic-mavros-msgs -y
wget https://raw.githubusercontent.com/mavlink/mavros/master/mavros/scripts/install_geographiclib_datasets.sh
sudo bash ./install_geographiclib_datasets.sh   

rviz安装

sudo apt-get install ros-noetic-rviz -y

pcl安装

sudo apt -y install libpcl-dev
sudo apt install ros-noetic-pcl-conversions -y

修改cpp中node_vis.header.frame_id = "world";

rqt_graph安装

sudo apt-get install ros-noetic-rqt-graph -y

docker支持gpu需要以下配置：

注意：docker run 需要添加参数 --gpus all

容器内可以读显卡

nvidia-smi

CUDA Toolkit安装 只装Base Installer CUDA 工具包包含创建、构建和运行 CUDA 应用程序所需的 CUDA 驱动程序和工具以及库、头文件和其他资源

验证CUDA是否安装成功

/usr/local/cuda/bin/nvcc --version

vim ~/.bashrc添加CUDA进环境

export PATH=/usr/local/cuda-12.3/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-12.3/lib64\
${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

CUDA安装

conatiner-toolkit安装？这个不知道装了有什么用

安装PaddlePaddle的gpu版本（CUDA10.2）

sudo apt-get update
sudo apt-get install git -y
sudo apt-get install python3-pip -y
sudo apt-get install ubuntu-drivers-common -y
python3 -m pip install paddlepaddle-gpu==2.3.2 -i https://mirror.baidu.com/pypi/simple

python3 -c "import paddle; print(paddle.__version__)"

安装Paddledection

# Clone PaddleDetection repository
cd <path/to/clone/PaddleDetection>
git clone https://github.com/PaddlePaddle/PaddleDetection.git

# Install other dependencies
cd PaddleDetection
pip install -r requirements.txt

# Compile and install paddledet
python3 setup.py install

sudo apt-get update
sudo apt-get install libgl1-mesa-glx
pip install numba==0.56.4
sudo apt-get install wget

# After installation, make sure the tests pass:
python3 ppdet/modeling/tests/test_architectures.py