Ubuntu18.04/20.04/22.04的Apollo8.0软件包安装(免编译)

news2024/12/22 18:51:49

本文主要介绍在如何使用软件包(即 deb 包)的方式来安装 Apollo,相对于源码方式安装,软件包安装方式不需要编译,更加快捷。但是对环境的支持比较单一,如果在自定义环境内安装,请移步源码安装方式

步骤一:安装基础软件

1. 安装 Ubuntu Linux

安装 Ubuntu 18.04+ 的步骤,参见 官方安装指南。

完成安装后更新相关软件:

sudo apt-get update
sudo apt-get upgrade

注意:若要完成更新,需要保证网络连接。

2. 安装 Docker Engine

Apollo 依赖于 Docker 19.03+。安装 Docker 引擎,您可以根据官方文档进行安装:

参见 Install Docker Engine on Ubuntu。
您还可以者通过 Apollo 提供的安装脚本直接安装:

wget http://apollo-pkg-beta.bj.bcebos.com/docker_install.sh
bash docker_install.sh

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这个过程可能会运行多次脚本,根据脚本提示执行即可,如下图提示再执行一次
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再次执行后输出docker is OK即可

bash docker_install.sh

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步骤二:安装 Apollo 环境管理工具

Apollo 环境管理工具是一个帮忙管理和启动 Apollo 环境容器的命令行工具。

1. 添加 apt 源

添加源和 key:

sudo bash -c "echo 'deb https://apollo-pkg-beta.cdn.bcebos.com/neo/beta bionic main' >> /etc/apt/sources.list"
wget -O - https://apollo-pkg-beta.cdn.bcebos.com/neo/beta/key/deb.gpg.key | sudo apt-key add -
sudo apt update

2. 安装 apollo-neo-env-manager

执行以下命令安装:

sudo apt install apollo-neo-env-manager-dev

成功安装后即可使用

aem -h

如果您对 aem 工具的功能感兴趣,可以查阅 aem - Apollo 环境管理工具。

步骤三(可选):获取 GPU 支持

Apollo某些模块需要GPU的支持才能够编译、运行(例如感知模块),如果您需要使用此类模块,需要安装Nvidia显卡驱动以及Nvidia container toolkit以获取GPU支持。

1. 安装显卡驱动

超详细ubuntu20.04/22.04安装nvidia驱动/CUDA/cudnn

安装完毕后,您可以通过nvidia-smi指令来检查驱动是否安装成功,如果一切正常,您可以看到类似以下的提示:
在这里插入图片描述

2. 安装 Nvidia container toolkit

为了在容器内获得 GPU 支持,在安装完 docker 后需要安装 NVIDIA Container Toolkit。 运行以下指令安装 NVIDIA Container Toolkit:

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) 
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - 
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list 
sudo apt-get -y update 
sudo apt-get install -y nvidia-docker2

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安装完毕后,需要手动重启下docker:

sudo systemctl restart docker

步骤四:创建和进入 Apollo 环境容器

1. 创建工作空间

创建并进入目录

mkdir application-demo
cd application-demo

2. 启动 apollo 环境容器

aem start

注意:默认的环境镜像已经包含 gpu 相关的依赖库,如您想以 gpu 模式启动容器可以使用start_gpu子命令。在使用start_gpu命令前,请务必确保已正确安装Nvidia显卡驱动以及Nvidia container toolkit

第一次执行该命令时会拉取docker镜像,并安装相关库文件

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[INFO] Determine whether host GPU is available ...
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Status: Downloaded newer image for registry.baidubce.com/apollo/apollo-env-gpu:latest
registry.baidubce.com/apollo/apollo-env-gpu:latest
[INFO] Remove existing Apollo Development container ...
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+ docker run -itd --privileged --name apollo_neo_dev_gnsf -e DISPLAY=:1 -e DOCKER_USER=gnsf -e USER=gnsf -e DOCKER_USER_ID=1000 -e HISTFILE=/apollo_workspace/.cache/.bash_history -e DOCKER_GRP=gnsf -e DOCKER_GRP_ID=1000 -e DOCKER_IMG=registry.baidubce.com/apollo/apollo-env-gpu:latest -e USE_GPU_HOST=1 -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=compute,video,graphics,utility -v /dev:/dev -v /media:/media -v /tmp/.X11-unix:/tmp/.X11-unix:rw -v /etc/localtime:/etc/localtime:ro -v /usr/src:/usr/src -v /lib/modules:/lib/modules --net host -w /apollo_workspace --add-host in-dev-docker:127.0.0.1 --add-host gnsf:127.0.0.1 --hostname in-dev-docker --shm-size 2G --pid=host -v /home/gnsf/apollo/application-demo:/apollo_workspace -v /home/gnsf/apollo/application-demo/data:/apollo/data -v /home/gnsf/apollo/application-demo/output:/apollo/output -v /home/gnsf/apollo/application-demo/data/log:/opt/apollo/neo/data/log -v /home/gnsf/apollo/application-demo/data/calibration_data:/apollo/modules/calibration/data -v /home/gnsf/apollo/application-demo/data/map_data:/apollo/modules/map/data -v /opt/apollo/neo/packages/env-manager-dev/1.0.0.5:/opt/apollo/neo/packages/env-manager-dev/1.0.0.5 -v /dev/null:/dev/raw1394 registry.baidubce.com/apollo/apollo-env-gpu:latest /bin/bash
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mkdir: created directory '/opt/apollo/neo/etc'
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apollo-neo-common-msgs-dev is already the newest version (1.0.0.1).
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cyber/
cyber/proto/
cyber/proto/choreography_conf_pb2.py  9,671 100%    0.00kB/s    0:00:00 (xfr#1, to-chk=31/36)
cyber/proto/classic_conf_pb2.py  8,687 100%    8.28MB/s    0:00:00 (xfr#2, to-chk=30/36)
cyber/proto/clock_pb2.py  2,017 100%    1.92MB/s    0:00:00 (xfr#3, to-chk=29/36)
cyber/proto/component_conf_pb2.py  9,232 100%    8.80MB/s    0:00:00 (xfr#4, to-chk=28/36)
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cyber/proto/record_pb2.py  36,848 100%   35.14MB/s    0:00:00 (xfr#11, to-chk=21/36)
cyber/proto/role_attributes_pb2.py  10,464 100%    9.98MB/s    0:00:00 (xfr#12, to-chk=20/36)
cyber/proto/run_mode_conf_pb2.py  4,729 100%    4.51MB/s    0:00:00 (xfr#13, to-chk=19/36)
cyber/proto/scheduler_conf_pb2.py  8,545 100%    8.15MB/s    0:00:00 (xfr#14, to-chk=18/36)
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cyber/python/cyber_py3/cyber_timer.py  2,895 100%    2.76MB/s    0:00:00 (xfr#23, to-chk=7/36)
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sent 14,810,388 bytes  received 621 bytes  29,622,018.00 bytes/sec
total size is 14,804,632  speedup is 1.00
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[WARN] the links of pre-version will be overwrited!
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modules/
modules/common/
modules/common/adapter/
modules/common/adapter/proto/
modules/common/adapter/proto/adapter_config_pb2.py  24,759 100%    0.00kB/s    0:00:00 (xfr#1, to-chk=8/18)
modules/common/latency_recorder/
modules/common/latency_recorder/proto/
modules/common/latency_recorder/proto/latency_record_pb2.py  15,018 100%   14.32MB/s    0:00:00 (xfr#2, to-chk=6/18)
modules/common/util/
modules/common/util/testdata/
modules/common/util/testdata/simple_pb2.py  5,074 100%    4.84MB/s    0:00:00 (xfr#3, to-chk=4/18)
modules/common/vehicle_model/
modules/common/vehicle_model/proto/
modules/common/vehicle_model/proto/vehicle_model_config_pb2.py  10,169 100%    9.70MB/s    0:00:00 (xfr#4, to-chk=2/18)
modules/common/vehicle_state/
modules/common/vehicle_state/proto/
modules/common/vehicle_state/proto/vehicle_state_pb2.py 10,207 100%    9.73MB/s    0:00:00 (xfr#5, to-chk=0/18)
sent 66,096 bytes  received 167 bytes  132,526.00 bytes/sec
total size is 65,227  speedup is 0.98
[INFO] symbolic links of common-dev created.
Setting up apollo-neo-buildtool-dev (1.0.0.8) ...
[INFO] start to create symbolic links of buildtool-dev
[WARN] the links of pre-version will be overwrited!
Looking in indexes: https://mirror.baidu.com/pypi/simple/
Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (2.27.1)
Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.6/dist-packages (from requests) (2.0.12)
Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests) (2022.12.7)
Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests) (2.6)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests) (1.26.13)
[INFO] symbolic links of buildtool-dev created.
Processing triggers for libc-bin (2.27-3ubuntu1.6) ...
[ OK ] Congratulations! You have successfully finished setting up Apollo Dev Environment.
[ OK ] To login into the newly created apollo_neo_dev_gnsf container, please run the following command:
[ OK ]   aem enter
[ OK ] Enjoy!

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如果一切正常,将会见到类似下图的提示:

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3. 进入 apollo 环境容器

aem enter

脚本执行成功后,将显示以下信息,您将进入 Apollo 的运行容器:

user_name@in-dev-docker:/apollo_workspace# 

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工作空间文件夹将被挂载到容器的 /apollo_workspace 中。

4. 初始化工作空间

aem init

在这里插入图片描述

至此 Apollo 环境管理工具及容器已经安装完成,接下来请跟着 QuickStart 文档根据不同的使用场景按需安装不同的模块。

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