Run OpenClaw on Raspberry Pi 5, NVIDIA Jetson Nano, and Jetson Orin for ultra-low-latency edge robotics. This guide covers ARM-specific installation, GPIO and CAN bus integration, performance tuning, and selecting the right edge board for your robot application.
Yes. OpenClaw supports Raspberry Pi 5 (8 GB RAM recommended) running either Raspberry Pi OS Bookworm (64-bit) or Ubuntu 22.04 Server ARM. Install using the ARM APT repository: add the openclaw-arm repository, set OPENCLAW_ARCH=aarch64 in your environment, then run sudo apt install openclaw. Note: the Bullet physics simulator is limited to 10 Hz on Pi 5 due to CPU constraints; use cloud or Jetson Orin for full-speed simulation alongside hardware control.
Flash the Jetson Nano with JetPack 5.1.3 (Ubuntu 20.04 ARM base). Install CUDA dependencies: sudo apt install cuda-toolkit-11-4. Add the OpenClaw repository for ARM: export OPENCLAW_ARCH=aarch64 && curl -fsSL https://apt.openclaw.dev/key.gpg | sudo gpg --dearmor -o /etc/apt/keyrings/openclaw.gpg && echo "deb [arch=arm64 signed-by=/etc/apt/keyrings/openclaw.gpg] https://apt.openclaw.dev stable main" | sudo tee /etc/apt/sources.list.d/openclaw.list && sudo apt update && sudo apt install openclaw openclaw-cuda.
Flash Jetson Orin with JetPack 6.1 (Ubuntu 22.04 ARM). Install: sudo apt install openclaw openclaw-cuda openclaw-tensorrt. The openclaw-tensorrt package enables TensorRT-accelerated AI model inference for vision-guided manipulation. Run openclaw sim --check-gpu to confirm Jetson's iGPU is detected. Expected performance: 30 Hz physics simulation alongside real-time hardware control at 1 kHz.
Raspberry Pi 5 costs $80 and handles robot communication, driver logic, and basic pick-and-place workflows at low cost. Jetson Orin Nano costs $250 and adds 40 TOPS of AI inference for on-device vision models and faster physics simulation. Choose Pi 5 for budget-constrained educational or simple industrial use cases; choose Jetson Orin when running vision-guided manipulation, neural-network grasping, or multi-robot coordination on the edge.
Install the openclaw-gpio plugin: sudo apt install openclaw-gpio. Configure in /etc/openclaw/config.yaml: gpio: emergency_stop_pin: 17 input_mode: pull_up active_low: true. Restart the OpenClaw service: sudo systemctl restart openclaw. The GPIO plugin monitors GPIO pin 17 and triggers an immediate safe stop when the pin goes low, enabling a physical emergency-stop button. Test with: openclaw gpio --test-pin 17.
Attach an MCP2515 CAN HAT and enable SPI in /boot/config.txt: dtparam=spi=on and dtoverlay=mcp2515-can0,oscillator=12000000,interrupt=25. Load the can module: sudo modprobe can && sudo modprobe can_raw && sudo modprobe mcp251x. Bring up the interface: sudo ip link set can0 up type can bitrate 1000000. In OpenClaw config set: gripper_driver: can_bus can_interface: can0 can_device_id: 0x001. Latency over CAN at 1 Mbit/s is under 1ms.
Enable the included systemd service: sudo systemctl enable openclaw && sudo systemctl start openclaw. View logs with: journalctl -u openclaw -f. Configure watchdog restart in /lib/systemd/system/openclaw.service by verifying the Restart=on-failure and RestartSec=5 directives are present. The service file automatically sets OPENCLAW_ARCH=aarch64 and sources the robot configuration from /etc/openclaw/config.yaml.
Cloud-hosted OpenClaw introduces 5 to 50ms network round-trip latency between the API server and the robot hardware driver, depending on VPN quality. Edge-deployed OpenClaw on Pi 5 or Jetson Orin runs the API server co-located with the hardware driver, delivering sub-millisecond internal API latency. For force-controlled manipulation or high-speed pick-and-place requiring control loop rates above 100 Hz, edge deployment is mandatory.
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