Jetson AGX Orin — Setup from Scratch

Complete guide for setting up the Jetson AGX Orin with NVMe boot and all software for the autonomous kart.

Hardware Overview

Component	Value
Board	NVIDIA Jetson AGX Orin Developer Kit
Architecture	aarch64 (ARM64), 12 CPU cores, 62 GB RAM
GPU	Ampere (CUDA 12.6)
Storage	57 GB eMMC (soldered) + 476 GB NVMe M.2 SSD
Display	DisplayPort only (no HDMI). Requires DP-to-HDMI adapter
Camera	ZED 2 stereo (USB)
CAN bus	can0, can1 (for ESP32 communication)

Boot Chain

The Orin uses three storage devices to boot:

QSPI flash (on-chip)     →  First-stage bootloader (firmware)
eMMC (57 GB, soldered)    →  Second-stage bootloader + boot partition
NVMe M.2 SSD (476 GB)    →  Ubuntu root filesystem (where the OS lives)

Boot sequence: QSPI → eMMC bootloader → NVMe root filesystem

• QSPI: Tiny on-chip flash. Holds the first code the CPU runs at power-on.
• eMMC: Internal storage soldered to the board. After NVMe flash, it only holds a small bootloader — not a full OS.
• NVMe: The M.2 SSD plugged into the board. This is where Ubuntu and all software lives, with ~435 GB available.

The flash tool writes to all three. This is expected.

Verify NVMe boot

After setup, df -h / should show /dev/nvme0n1p1, NOT /dev/mmcblk0p1.

Software Stack

Software	Version	Installed via
JetPack	6.2.2 (L4T R36.5)	Flash (see below)
Ubuntu	22.04	Flash
CUDA	12.6	sudo apt install nvidia-jetpack
cuDNN	9.x	sudo apt install nvidia-jetpack
TensorRT	10.x	sudo apt install nvidia-jetpack
ROS 2	Humble	apt (ROS 2 repos)
ZED SDK	4.2	Installer from Stereolabs (L4T 36.4 build, compatible with 36.5)
PyTorch	2.10	NVIDIA Jetson AI Lab wheels
Python	3.10 (system)	Pre-installed

Why ZED SDK 4.2 and not 5.2?

ZED SDK 5.2 does not provide a build for L4T 36.5 as of February 2026. The 4.2 build for L4T 36.4 installs successfully on L4T 36.5 with a compatibility warning. Upgrade when a 5.2 build for L4T 36.5 becomes available.

Why JetPack 6.2.2 and not JetPack 7?

JetPack 7 does not support AGX Orin as of February 2026. Only the newer Jetson Thor family is supported. Orin support is expected in JetPack 7.2 (Q2 2026). Our full stack (ROS 2 Humble, ZED SDK, PyTorch, YOLOv5) is confirmed compatible with JetPack 6.2.2.

Flashing to NVMe

What you need

• Flash host: x86_64 Linux machine (Ubuntu 22.04 or 24.04). We use the y540 laptop.
• USB-C cable: Data-capable (not charge-only)
• Monitor + keyboard: For the first-boot setup wizard

Step 1: Prepare the flash host

# Install dependencies
sudo apt-get install -y abootimg binfmt-support binutils cpio cpp \
  device-tree-compiler dosfstools lbzip2 libxml2-utils nfs-kernel-server \
  python3-yaml sshpass udev

# Download L4T R36.5 BSP and root filesystem (~2.4 GB total)
mkdir -p ~/jetson-flash && cd ~/jetson-flash
wget https://developer.nvidia.com/downloads/embedded/l4t/r36_release_v5.0/release/Jetson_Linux_r36.5.0_aarch64.tbz2
wget https://developer.nvidia.com/downloads/embedded/l4t/r36_release_v5.0/release/Tegra_Linux_Sample-Root-Filesystem_r36.5.0_aarch64.tbz2

# Extract
tar xf Jetson_Linux_r36.5.0_aarch64.tbz2
sudo tar xpf Tegra_Linux_Sample-Root-Filesystem_r36.5.0_aarch64.tbz2 -C Linux_for_Tegra/rootfs/
cd Linux_for_Tegra/
sudo ./tools/l4t_flash_prerequisites.sh
sudo ./apply_binaries.sh

Step 2: Put the Orin in Recovery Mode

Connect the USB-C cable from the flash host to the Orin's flashing port (the USB-C port next to the 40-pin GPIO header, NOT the power port).

If the Orin is powered off:

1. Press and hold the Force Recovery button (middle button)
2. Power on (press the Power button)
3. Release both buttons after ~2 seconds

If the Orin is powered on:

1. Press and hold the Force Recovery button (middle button)
2. Press and release the Reset button (leftmost button)
3. Release the Force Recovery button after ~2 seconds

Verify on the flash host:

lsusb | grep -i nvidia
# Should show: 0955:7023 NVIDIA Corp. APX  (recovery mode)
# NOT: 0955:7020  (normal mode)

Step 3: Flash

cd ~/jetson-flash/Linux_for_Tegra

sudo ./tools/kernel_flash/l4t_initrd_flash.sh \
  --external-device nvme0n1p1 \
  -c tools/kernel_flash/flash_l4t_t234_nvme.xml \
  --showlogs \
  -p "-c bootloader/generic/cfg/flash_t234_qspi.xml" \
  --network usb0 \
  jetson-agx-orin-devkit \
  nvme0n1p1

This takes ~10-20 minutes. The output ends with Flash is successful.

Step 4: First boot

First boot takes time

After flash, the Orin takes ~5 minutes with no display signal while initializing. If no signal after 5 minutes, power cycle (hold power button 5 seconds, then press again). After power cycle, BIOS appears in seconds, then Ubuntu boots in ~2 minutes. There may be brief periods of no signal during boot — this is normal.

Complete the Ubuntu setup wizard:

• Username: orin
• Password: 0
• Computer name: orin

Post-Flash Software Installation

After the first-boot wizard, install everything:

1. JetPack SDK (CUDA, cuDNN, TensorRT)

sudo apt-get update
sudo apt-get install -y nvidia-jetpack

This is a large install (~5-7 GB). Verify:

nvcc --version   # Should show CUDA 12.6
dpkg -l | grep tensorrt   # Should show TensorRT 10.x

2. ROS 2 Humble

sudo apt install -y software-properties-common curl
sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key \
  -o /usr/share/keyrings/ros-archive-keyring.gpg
echo "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/null
sudo apt-get update
sudo apt-get install -y ros-humble-desktop ros-humble-vision-msgs ros-dev-tools
echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc

3. ZED SDK

cd /tmp
wget -q "https://download.stereolabs.com/zedsdk/4.2/l4t36.4/jetsons" -O ZED_SDK.run
chmod +x ZED_SDK.run
./ZED_SDK.run -- silent skip_tools skip_samples

4. PyTorch

pip3 install --no-cache-dir \
  --extra-index-url https://pypi.jetson-ai-lab.dev/jp6/cu126 \
  torch torchvision
pip3 install --no-cache-dir 'numpy<2' ultralytics pyyaml

numpy must be < 2

OpenCV on the Jetson was compiled against numpy 1.x. Installing numpy 2 will break cv2.

5. Clone and build kart_brain

cd ~
git clone git@github.com:UM-Driverless/kart_brain.git
cd kart_brain
source /opt/ros/humble/setup.bash
colcon build
echo "source ~/kart_brain/install/setup.bash" >> ~/.bashrc

6. AnyDesk (remote desktop)

curl -fsSL https://keys.anydesk.com/repos/DEB-GPG-KEY \
  | sudo gpg --dearmor -o /usr/share/keyrings/anydesk-archive-keyring.gpg
echo "deb [arch=arm64 signed-by=/usr/share/keyrings/anydesk-archive-keyring.gpg] \
  http://deb.anydesk.com/ all main" \
  | sudo tee /etc/apt/sources.list.d/anydesk-stable.list > /dev/null
sudo apt-get update
sudo apt-get install -y anydesk

After installing AnyDesk, configure Xorg for headless operation (no physical monitor):

sudo mkdir -p /etc/X11/xorg.conf.d
sudo tee /etc/X11/xorg.conf.d/10-virtual-display.conf > /dev/null << 'EOF'
Section "Device"
    Identifier "Tegra"
    Driver "nvidia"
    Option "AllowEmptyInitialConfiguration" "true"
    Option "ConnectedMonitor" "DFP-0"
EndSection

Section "Screen"
    Identifier "Default Screen"
    Device "Tegra"
    DefaultDepth 24
    SubSection "Display"
        Depth 24
        Virtual 1920 1080
    EndSubSection
EndSection
EOF
sudo systemctl enable anydesk

Why ConnectedMonitor DFP-0?

The DP-to-HDMI adapter with a dummy HDMI plug doesn't provide proper EDID. Without this option, the NVIDIA driver sees both DFP-0 and DFP-1 as "disconnected", so Xorg has no screen and AnyDesk gets a black framebuffer. Forcing ConnectedMonitor DFP-0 makes the driver create a framebuffer on the DisplayPort output regardless.

Verification Checklist

• [ ] NVMe is root: df -h / shows /dev/nvme0n1p1
• [ ] CUDA: nvcc --version → 12.6
• [ ] TensorRT: dpkg -l | grep tensorrt → 10.x
• [ ] PyTorch GPU: python3 -c "import torch; print(torch.cuda.is_available())" → True
• [ ] ROS 2: ros2 --help
• [ ] ZED camera: ls /dev/video* (after plugging in)
• [ ] kart_brain built: ros2 pkg list | grep kart
• [ ] SSH access: ssh orin from Mac
• [ ] AnyDesk: working with dummy HDMI plug

Network Access

Method	Address	Notes
SSH (WiFi)	ssh orin (10.7.20.x, DHCP)	IP may change
SSH (Ethernet)	ssh orin_wire (10.0.255.177)	Static, cable required
AnyDesk	Via ID	Needs dummy HDMI plug

Always verify IPs

The Robots_urjc network uses DHCP. Run hostname -I on the Orin to get the current IP. Update ~/.ssh/config on your Mac if it changed.

Known Issues

Issue	Workaround
ZED needs re-plug after reboot	Unplug and replug USB
torch needs LD_LIBRARY_PATH	export LD_LIBRARY_PATH=/home/orin/.local/lib/python3.10/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH
numpy >= 2 breaks cv2	Pin to numpy<2
BGR/RGB swap in YOLO debug image	Fixed in yolo_detector_node.py — always convert RGB back to BGR before publishing as "bgr8"
No HDMI port	Use DP-to-HDMI adapter