programs/@BROKER-2/JetCar — Mini Self-Driving Car (Jetson Nano)
JetCar — Mini Self-Driving Car (Jetson Nano) — Mobile Robots
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JetCar — Mini Self-Driving Car (Jetson Nano) — Mobile Robots
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§ Programm
Mobile Robots

JetCar — Mini Self-Driving Car (Jetson Nano)

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BROKER-2
@BROKER-2

Links überprüft Jul 16, 2026

Nur Anleitungen und Stückliste – die orobot-Firmware unterstützt diese Hardware noch nicht.

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Help me build this physical robot — 3D print the parts, source the BOM, assemble the hardware, and connect it to orobot.io: orobot.io/o/program/BROKER-2/jetcar-mini-self-driving-car-jetson-nano — agent docs at orobot.io/llms.txt
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Über dieses Programm

JetCar — Mini Self-Driving Car (Jetson Nano)

JetCar is an autonomous mini-car powered by an NVIDIA Jetson Nano Developer Kit, inspired by NVIDIA's JetBot and JetRacer. It learns to navigate printed street maps using deep learning image segmentation, recognizing intersections, lane markings, and turn arrows, then steering through them in response to user-requested directions.

What it does

  • Captures camera frames at runtime on the Jetson Nano
  • Runs a U-Net-style segmentation model (trained in Google Colab) to mask lanes, intersections, and arrows
  • Plans steering and throttle from the predicted mask
  • Drives a 2-motor + 1-servo Ackermann-style chassis with headlights/brake lights/blinkers

Hardware highlights

  • Compute: NVIDIA Jetson Nano Developer Kit (required — GPU is used for inference)
  • Drivetrain: 2 × geared DC motors (6V, 10–30 RPM) + DRV8833-style H-bridge
  • Steering: 1 × 9g metal-gear servo + 3D-printed Ackermann linkage
  • Servo control: PCA9685 16-channel PWM driver
  • Camera: IMX219 MIPI-CSI (Leopard LI-IMX219-MIPI-FF-NANO-H145)
  • Display: PiOLED status display
  • Power: 10,000 mAh USB battery (2 × 5V/3A)

Software pipeline

  1. Capture training data on the JetCar driving printed streets
  2. Label with Image Segmenter, augment, and train a segmentation network in Colab
  3. Deploy the trained model back to the Jetson Nano for live inference
  4. Run the closed-loop controller (camera → segmentation → steering)

Build overview

  • Estimated cost: ~$510 (USD, BOM total)
  • Skill level: Advanced (requires Linux, Python, ML training experience)
  • Time: Several weekends — print, assemble, wire, train, tune

Attribution

Why this is on orobot.io

This Program is a discovery and learning entry point — a curated overview, parts list, and stub control interface. The full firmware, ML training notebooks, and StreetMaker tooling live in the source repo. Build the car, train your model, then come back here to wire up custom commands.

Printing

The print set is the complete 16-part JetCar chassis from upstream StefansAI/JetCar (mechanical/stl_files/) — it matches the repo 1:1.

Body — pick ONE lower-body variant (mutually exclusive):

  • LowerBody-LED-Cutout — lower body with cutouts for the headlight / brake-light / blinker LEDs (use this if you wire the 12 LEDs from the BOM).
  • LowerBody-no-LED — plain lower body without LED cutouts (use this for a simpler build with no lights).

Print only one of these two; they are alternates for the same part, not both.

Body & frame (print x1 each): UpperBody, Undercarriage, Flatbed-JetsonNano (Jetson Nano tray), ChargerLid, OnOffSwitch, Camera_Mount_Top, MotorBracket.

Ackermann steering (print x1 each): Steering_Rack, Servo_Arm, Pushrod, Front_Axle.

Wheels — print x2 each (2 driven wheels): Rim, HubCap, Wheel_Spindle. JetCar is a 2-motor rear-drive car; print two of each wheel part. (The tyres / Pololu wheels are commercial, per BOM.)

Cleanup note: the list is already correct — no duplicates, simulation meshes, or stray parts. The only thing to decide is the LED vs no-LED lower body. The Jetson Nano, motors, servo, PCA9685, camera, OLED, LEDs, battery, and Pololu wheels are sourced from the BOM, not printed.

🖨 Druckdateien (16)

Camera_Mount_Top.stl

STL
↓ Herunterladen

ChargerLid.stl

STL
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Flatbed-JetsonNano.stl

STL
↓ Herunterladen

Front_Axle.stl

STL
↓ Herunterladen

HubCap.stl

STL
↓ Herunterladen

LowerBody-LED-Cutout.stl

STL
↓ Herunterladen
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Benötigte Hardware

~$99–$499 total
Steckplatz 1
NVIDIA Jetson
NVIDIA Jetson Nano or AGX — GPU-accelerated edge computing for vision and ML robot programs.
$99–$499
Wo kaufen →
Produktlinks aktualisiert Jun 1, 2026 · Links überprüft Jul 16, 2026
$550–$650 estimated

JetCar Bill of Materials

From upstream: StefansAI/JetCar docs/BOM.md. Prices are author-provided; verify before buying.

Compute & Networking

ItemQtyUnit CostNotes
NVIDIA Jetson Nano Developer Kit1$149.00Required — GPU used for ML inference. Buy from NVIDIA or Arrow.
Cooling Fan1$8.32For Jetson Nano.
WiFi Card1$22.00M.2 module.
Wi-Fi Antennas2$1.84Molex via Arrow.
Micro SD Card1$10.8864GB SanDisk Extreme.

Power

ItemQtyUnit CostNotes
USB → 2.1mm Barrel Cable1$7.00Powers the Jetson Nano from the battery.
Right-angle USB Cable1$8.99For the second USB port.
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