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nvidia@nvidia-desktop:~$ head -n 1 /etc/nv_tegra_release
# R35 (release), REVISION: 4.1, GCID: 33958178, BOARD: t186ref, EABI: aarch64, DATE: Tue Aug  1 19:57:35 UTC 2023
nvidia@nvidia-desktop:~$ sudo apt-cache show nvidia-jetpack | grep Version
[sudo] nvidia 的密码： 
Version: 5.1.2-b104
nvidia@nvidia-desktop:~$

# 创建虚拟环境 (名为 .venv)（下面保留主环境库）
python3 -m venv .venv
python3 -m venv --system-site-packages .venv
# 激活环境
source .venv/bin/activate
# 退出激活
deactivate

services:
  ros2_slam:
    image: ros:humble-perception
    container_name: ros2_slam
    tty: true
    stdin_open: true
    network_mode: host
    ipc: host
    privileged: true
    volumes:
      - /dev:/dev
      - ./ros2_ws:/root/ros2_ws
    environment:
      - ROS_DOMAIN_ID=0
      - RMW_IMPLEMENTATION=rmw_fastrtps_cpp
    working_dir: /root
    command: bash

docker run -d \
  --name code-server-gpu \
  --runtime nvidia \
  --gpus all \
  --security-opt seccomp=unconfined \
  -p 8080:8080 \
  -p 1000:6080 \
  -p 1001:5900 \
  -p 1002:8888 \
  -p 1003:80 \
  -p 1004:443 \
  -p 1005:3000 \
  -v "/home/nvidia/taospace/code-server/config:/home/coder/.config" \
  -v "/home/nvidia/taospace/code-server/project:/home/coder/project" \
  -e AUTH=password \
  -e PASSWORD=password \
  -e DISPLAY=:99 \
  -u "$(id -u):$(id -g)" \
  --restart always \
  codercom/code-server:latest \
  --cert

docker run -it -d \
  --name ros_gpu_final \
  --runtime nvidia \
  --gpus all \
  --network host \
  --shm-size=16gb \
  -e NVIDIA_VISIBLE_DEVICES=all \
  -e NVIDIA_DRIVER_CAPABILITIES=compute,graphics,display,utility,video \
  -e DISPLAY=:99 \
  dustynv/ros:humble-desktop-pytorch-l4t-r35.4.1

head -n 1 /etc/nv_tegra_release

sudo apt-cache show nvidia-jetpack | grep Version

sudo nano /etc/modprobe.d/blacklist-ucsi_ccg.conf

blacklist ucsi_ccg

sudo update-initramfs -u

sudo reboot