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Duckiebot (DB-J)

Duckiebot (DB-J)

Regular price $469 USD
Regular price Sale price $469 USD
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Computation
Assembly

Bring your vehicle autonomy education and research to the next level with the latest Duckiebot model!

This DIY kit provides a fully-programmable model self-driving car featuring: 

  • Mature design: quality stemming from years of iterations and feedback from thousands of users, from top university Professors to young learners, and everybody in between 
  • Chassis:
    • Differential drive configuration

  • Sensors:
    • Hall effect sensor wheel encoders
    • Front-facing 160deg FOV camera
    • Inertial Measurement Unit (IMU)
    • Front-facing time of flight sensor
    • Battery diagnostics

  • Actuators:
    • 2 DC motors
    • 4 Addressable RGB LEDs (controllable in intensity, color, and frequency)

  • Computation:
    • NVIDIA Jetson Nano 4GB (Jetson Nano 2GB is supported)
    • Currently available with original NVIDIA Jetson Nano 4GB modules and non-official carrier boards only (performance guaranteed by Duckietown!)
  • Memory:
    • (Fast) 64 GB micro SD card, class 10, U3

  • Power:
    • Smart Duckiebattery: 10Ah, 2x2A USB outputs, 4.5A max
      • Provides live diagnostics and soft shutdown
  • User Interface:
    • Screen
    • Shut-down button

  • Complete: all components needed to assemble and calibrate your Duckiebot come in the box. Power adapter not included (5V, 2A, micro-USB recommended).

  • No soldering is required

  • MOOC compliant: -J4 is recommended to join the Duckietown online learning experience.  You will need a city track as well, check out the "MOOC Founder's edition kit" for a one-click solution.  

Have a Jetson Nano already? Select the "No Jetson" variant.

What's in the box

  • 1x Bottom deck
  • 2x Lower lateral supports
  • 1x Middle deck
  • 1x Upper-left lateral support
  • 1x Upper-right lateral support
  • 1x Back support
  • 1x Top deck
  • 1x Back pattern plate
  • 2x Motor mounts
  • 1x Camera mount
  • 1x Front bumper (FB) PCB
  • 1x Back bumper (BB) PCB
  • 1x Omni-wheel
  • 2x Front wheels
  • 2x DC Motors with Encoders
  • 1x Jetson Nano camera
  • 1x Camera cable
  • 1x Inertial Measurement Unit (IMU)
  • 1x Time of flight (ToF) sensor
  • 1x Jetson Nano 2GB (JN2), Jetson Nano 4GB (JN4) or No Jetson (variants)
  • 1x Duckietown Hut v 3.15
  • 1x 64GB Class 10 U3 micro SD card
  • 1x Duckiebattery
  • 1x WiFi dongle
  • 1x Screen
  • 1x Shutdown button
  • 1x DC fan
  • 1x FCC label sticker
  • 1x Cross screwdriver
  • 1x Camera calibration pattern
  • 1x Micro SD to USB adaptor
  • 1x Back pattern sticker
  • 3x Metal stand-off M2.5x18+6mm M-F
  • 3x Metal hexagon stand-off M3 25mm F-F
  • 2x Spacer M6x12x1.5
  • 4x Nylon screw M2x8
  • 14x Nylon screw M2.5x12
  • 2x Round head tapping screws metal (3x20)
  • 4x Metal screw M3x30
  • 30x Metal screw M3x12
  • 30x Metal nut M3
  • 16x Nylon nut M2.5
  • 4x Nylon nut M2
  • 1x Jetson - Battery cable
  • 1x Battery - HUT(Ext5V) power cable
  • 1x HUT - Battery charging cable
  • 1x HUT to BB cable
  • 2x Motor - HUT cables
  • 1x FB to ToF cable
  • 3x HUT to FB, IMU cable
  • 1x Screen - HUT cable
  • 1x Button - HUT cable
  • 2x Duckies
  • 1x Instructions card
  • 2x Duckietown Stickers

Frequently asked questions

What can I do with Duckietown?

Duckietown is an open platform, so you can implement virtually anything on it. We provide a number of learning experiences to start from, to guide users from the first steps to autonomous behaviors.

A unique perk of using Duckiebots is that you can start learning immediately with "Self-Driving Cars with Duckietown", a user-paced polished online course that we make available for free on the edX platform.

TeachStart here to teach a state-of-the-art robot autonomy class.

How do I get help?

Duckietown has a large community of users and detailed documentation that should be sufficient to address the most common issues. To ask for community support:

Step 1: Join the Duckietown Slack

Step 2: Follow the instructions inside Slack and join our Stack Overflow space.

Step 3. Search on Stack Overflow for questions and answers. Post your question there if you cannot find your problem already solved.

Step 4. Sometimes it is more convenient to interact at a faster pace, e.g., if debugging some issue. We use Slack to do so. Link the Stack Overflow question you created inside the most appropriate #help channel on Slack to jumpstart the conversation.

Note: Duckietown prioritizes providing support in the following order: (a) priority support customers; (b) Stack Overflow questions; (c) Slack questions; (d) questions via email (please don't email us with tech support questions!)

If you are planning to teach with Duckietown or set up a lab, consider purchasing the respective subscription to receive priority support, as Duckietown staff cannot otherwise guarantee a timely response.

I can't find the chassis inside the box. Where is it?

The chassis is underneath the white protection foam inside the box. Lift it up to access the chassis components.

Dimensions

Dimension: 13x6x9'' (34x15x23cm)
Weight: 4 lbs (1.8 kg)

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Customer Reviews

Based on 3 reviews
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F Abawi
A useful tool for robot enthusiasts with a duckie on top

The duckiebot is a cost-effective product for those wanting to develop or explore working with robotics, especially tasks such as robot navigation, autonomous driving, sensing and actuating, and middleware (ROS) usage understanding/learning. Also, given that everything is open-source, you can integrate it with any platform or framework you'd like. I also enjoyed the robot assembly a lot. Highly recommended for pros and hobbyists alike

F
Fernando Bordignon
Duckietown: a good artifact for enjoy and learning

Thanks for creating this object. I believe in its possibilities in education and look forward to adopting it in my classes.

S
Sampsa Ranta
Duckiebots are great!

When I was looking for different robots with Jetson Nano for putting some computer vision into action.. I came to choose Duckiebot as it has motors with encoders and also Duckietown has MOOC course. MOOC course works perfect as guided tour into realm of ducks.

Before Duckiebot I've tried some robot solutions with micro-Python, but I found the platform quite restrictive for my use due to much more restricted computing power and software stacks. Duckietown has developed learning environment with baseline algorithms.

The current environment is mostly ROS 1 and on MOOC Python is used.

In picture is my Duckiebot Duckgull DB21J4 (with Jetson Nano 4GB).