Rover V2 four wheel drive robot

Rover is a big four wheel drive 3D printed robot you can make at home. It's CC0 open source, so anyone can use it.

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Rover is a 3D printed four wheel drive robot you can make in a small shop.I made the vehicle so I can use it for computer vision research. Specifically, I want to experiment with the use of low cost cameras for robot localization, navigation, and 3d obstacle avoidance.I make 3D printed robots with the hope that the hardware can more easily evolve over time as software does. I hope some day to start fully automated communities owned by the residents.The hardware is licensed CC0 and design files are in OnShape so anyone can fork the design and modify it for free. Software is a custom python stack for the raspberry pi, BSD licensed on GitHub.See relevant links in this projects details section. Rover is a project from

Rover's CAD work is done in OnShape, so anyone can fork the design for free. It's licensed CC0 so it can be used for any purpose with no restrictions. Get started with the files here:

Rover runs an open source licensed Python stack I wrote myself, and uses a Raspberry Pi for basic control. (Future versions may use a Jetson TX2 or similar.)

A video showing Rover V2's rolling chassis is here:

You can see the drive system for Rover V2 in use on V1 below. Note that Rover V2 uses the same motors, electronics, and code, but represents a full mechanical redesign of V1.

Rover has a parent website, called, with a discussion board where people can talk about 3D printing useful robots and what it all means. Visit that at

My long term goal with reboot is to make many useful open source robots, and then attempt to start communities where the robots support the survival of the community members by making them food and other useful goods. I discuss this concept in my essay The Machine.

Near term, I will use Rover to experiment with low cost sensing for robotics using simple cameras as the primary sensor in localization, obstacle avoidance, and navigation systems.

I started Rover V1 in Oct 2017 and had it driving by December. Work on Rover V2 started around the beginning of April 2018.

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  • IT'S ALIVE!!!!

    tlalexander06/06/2018 at 16:47 0 comments

  • Encoder calibration tutorial

    tlalexander06/06/2018 at 16:40 0 comments

    in this video I demonstrate the encoder calibration procedure using the open source VESC Tool software.

  • Encoder Magnet Installation Instructional Video

    tlalexander06/04/2018 at 06:34 0 comments

    Howdy Rover'ers!

    I've got another update on the project. This time I've made an instructional video showing how to super glue the magnet on to the end of the motor - a task necessary for operation of the encoder. The encoders on Rover (and other robots of mine like Skittles) give the motor controller precise control over motor torque, velocity, and position. This advanced control is critical to making safe, useful robots that can perform a wide variety of helpful tasks.

    Without further ado, check out the encoder magnet installation tutorial below:

    Thanks for watching and if you want to talk about Rover or help with the project, please visit and create an account today!


  • Video update and next steps

    tlalexander06/04/2018 at 02:12 0 comments

    Hey Hackaday Hackers!

    I've collected the robots I've been building over the last 7 months and made a short video. It's a good short overview of what I'm doing, and shows Rover V1 and Rover V2 together next to me for scale.

    So what's next for Rover V2? Over the next month or so, I will bring up the electronics and software on Rover V2 that I had originally on Rover V1. Rover V2 uses all the same motors, electronics, and software as V1 so it should be painless to get it operating under remote control. Take a look at V1 driving here:

    After I've brought up remote control on V2, I have a few tasks to work on next:

    • Bring up reinforcement learning in the simulator, so the virtual robot can follow trails.
    • Add a suitable camera system to Rover V2 and begin work to bring autonomy to the physical system.
    • Improve documentation for Rover's software control system, mechanical design, sensor setup, and electronics.
    • Expand outreach on Rover's home site,, to try to find collaborators who want to help make Rover better.

    Long term my goals are to build an open source farming system, and I see Rover V2 as a software research platform to develop some of the key algorithms a farming bot would need to navigate safely around a farm.

    If you like what you see, please share this project and consider creating an account on to help with the Rover project!

  • Rover Simulator now on Github!

    tlalexander06/04/2018 at 00:24 0 comments

    Hey Rover fans!

    I've now uploaded the files for Rover Sim to github. Please check them out, download them, and let me know if I missed anything! I am still learning how to use Unreal Engine, so if I left off any files I want to know!

  • Rover simulator, deep nets, navigation, and sensor plans.

    tlalexander06/02/2018 at 20:06 0 comments

    Hey Rover fans!

    I've started building a simulator for Rover using Unreal Engine. See the video of the simulator and my rationale and goals with the simulator below:

    I'd like to build a kind of next generation navigation stack for Rover that uses only cameras for localization, path following, and obstacle avoidance. I have experience bringing up ROS based navigation systems using LIDAR, but those systems are expensive and traditional mapping and localization algorithms for LIDAR are typically for indoor flat environments like offices. While working on a robotics project for my job two years ago, I was asked to survey all possible sensing modalities for a well funded commercial robot, and spent time looking at 3D LIDAR like the Velodyne Puck, Time of Flight cameras like the IFM 03D303 and Kinect V2, structured light cameras like the first generation Kinect and the old Asus Xtion Pro, stereo pair cameras like the ZED Stereo Camera and the Playstation 4 camera (which at $50 is a steal for linux based robotics if you don't mind wiring on a USB3 connector to the cable!), and more.

    I found that getting full 360 degree surround sensor coverage for the robot would be terribly expensive, the compute required to process all the data would be prohibitive for any semblance of a low cost system, the power budget would be terrible, and success in sunlight was still uncertain. Meanwhile stereo cameras looked almost do-able, but the quality of data one could glean with state of the art algorithms was so poor it seemed hopeless. It would be only $200 to surround the system with cameras compared to $10k for other sensors, but we couldn't make enough sense of the data to meet our operational needs. I surveyed the algorithms by looking at deployed systems, open source libraries, and the latest research, and it seemed there could be hope in the future for camera based systems. Indeed, most animals on Earth do well with just a pair of optical sensors and a movable head.

    More recently, deep neural networks have revolutionized the way computers understand images and the world around them. We no longer need to manually tune algorithms to detect features in an image based on a human understanding of the data. We are learning to train algorithms to find the necessary details on their own. This is an approach that is both far more accurate and more computationally efficient than past approaches. A low power computer chip is all that is needed to do person following on modern drones - a task that would have taken a desktop grade CPU just a few years ago.

    And so, I've envisioned the Rover system as a sort of camera-based research platform for robotics. Rover is made for unstructured off road environments, not flat well-behaved offices. I've come up with a six camera surround system I think has promise for a vehicle like this - four fish eye cameras in the corners and one regular view camera in the front and rear. This would allow Rover to do some stereo reconstruction of scenes while also giving it a monocular view all around the robot, with higher resolution images for front and rear just like the fovea in mammalian eyes.

    The hardware would be a Jetson TX2 computer with six cameras feeding in to its CSI camera bus. This is off the shelf hardware and I think the TX2 will be enough for some pretty solid navigation work. See one such camera system below:

    Rover Sim is a virtual environment designed to allow the development and training of the appropriate machine learning algorithms. It will be totally open source as soon as I get a little time to publish it on Github. Once the basic sim is complete (I need to modify the camera position to resemble Rover's planned camera placement), I will work on bringing up the World Models algorithm in sim:

    I will start by just following the black road in the Sim, a straightforward enough task by my estimation. From there I will spruce up the trails a bit, and retrain the World Model network to follow...

    Read more »

  • See Rover V2 at Maker Faire this weekend!

    tlalexander05/19/2018 at 07:08 0 comments

    Visit the Robot tent in Zone 5 and look for the yellow banner. There you can see Rover V1 and Rover V2 in person, as well as nab some of my propaganda writing in a new book I've printed. If you don't have the fortune of being in the area, catch my propaganda in this PDF here:

    Oh, you can also meet me! My brain is full of crazy ideas about robots - come ask me about them!

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  • 1
    Mechanical assembly instructions.

    Rover is characterized by four corner assemblies attached to a central frame. Build the corner assembly as follows:

    Print the sun, ring, and planet gears first. Then the planet carrier aka output, the gearbox cap, the wheel rim and wheel cap. 

    The first step in rover assembly is to install the sun on to the shaft adapter, and then install that on to the motor. You won’t have an opportunity to tighten the shaft adapter after the next step, so make sure it is secure.

    Next, use four M4 x 14mm screws to attach the motor to the ring gear. Then grab one suspension arm and a 6817 bearing, and install the bearing over the bearing support on the motor side of the suspension arm.

    Once the bearing is installed, carefully feed the wires of the motor through the wire feed hole in the suspension arm, making sure the wires are not jammed and you are able to push the ring gear and motor assembly flat against the support arm. Then install all of the screws to hold the ring gear on to the support arm. Be careful! One of the screw holes only has the motor wires behind it. Do not install a screw in that hole.

    Check that the motor can spin freely by spinning the sun gear with your fingers. If the motor rubs or does not rotate, figure out why and fix it before proceeding.

    Once the motor and ring gear assembly is secure, install the planets one by one in to the ring gear via the geared slot in the ring gear. After installing each planet, rotate the sun until that planet is 90 degrees off from where it started. Repeat this until the four gears are installed properly.

    If the planets are installed correctly, the planet carrier should drop in. Install the carrier with the bottom facing the gears.

    Take two 6808 bearings and place them in the gearbox cap. Then screw the cap on to the ring gear.

    Next, fit the big rim over the gearbox and on to the large bearing. Rotate the rim while installing it so the spline can mate to the gearbox. Then screw the hub cap on to the rim. One corner assembly is now complete. Do this four times, then attach the corner assembly to the main chassis. Once the corner assemblies are attached to the main chassis, use zip ties to secure the springs to the frame. You should now have a rolling chassis!

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Tim O'Brien wrote 08/24/2018 at 20:12 point

YESSS Taylor, great to see this in the wild! Oh, I've got a 1kg roll of petg 2.85mm I accidentally ordered that's yours if you want it! Print 1/8th of one of your parts :P

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