What to do if the Boston Dynamics robot dog costs 530,000 yuan?
Why not use an open-source project to DIY one with a Raspberry Pi, costing less than 4,000 yuan.
Doesn’t it feel like a Boston Dynamics dog?
First, let’s warm up and showcase the flexible joints:
By controlling the body posture with three axes, this Raspberry Pi version of the Boston Dynamics dog can achieve two types of movement modes.
One is the jogging posture. In this 4-phase gait, the two legs on the diagonal move simultaneously, allowing for faster movement speed.
The other is the walking posture. This 8-phase gait, combined with body movement, helps maintain the balance and stability of the robot dog.
This robot dog was built by a foreign guy Michael Romanko.
Are you feeling a bit excited?
Then keep reading to grab this detailed open-source tutorial, owning your own mini Boston Dynamics dog is not a dream. (Dog head)
Hardware costs less than 4000 yuan
This Raspberry Pi robot dog is built on the open-source ThingVerse Spot Micro framework. The shell is made using a 3D printer with a 0.6 nozzle.
The software runs on a Raspberry Pi 3B computer with Ubuntu 16.04.
So first, you need to prepare a Raspberry Pi 3B development board worth about 230 yuan.
The control components cost less than 30 yuan, and the interface is I2C with the servo driver PCA9685.
Additionally, 12 servo motors PDI-HV5523MG are needed, each priced at about 70+ yuan.
You also need to equip a 16×2 I2C interface LCD display.
For the battery, a 2s 4000mAh lithium battery is used, directly connected to the power servo, costing around 160 yuan.
The voltage regulator used is HKU5 5V/5A UBEC, which powers the Raspberry Pi, LCD panel, and PCA9695 control board, costing about 45 yuan.
The total cost, including the 3D printer, does not exceed 4000 yuan, even lower than the cost of Stanford’s low-cost open-source quadruped robot Pupper (600-1000 USD).
△ Stanford Pupper
Detailed tutorial down to every detail
Mike’s assembly tutorial is quite brief, but he provides a reference to a “mini robot dog AI” (SpotMicroAI) community.
The SpotMicroAI tutorial is “step-by-step,” where the engineer who wrote the tutorial provides detailed instructions for every step of assembling the robot dog, even including how to SSH into the Raspberry Pi, aiming for everyone to understand.
First, install the operating system on the Raspberry Pi, it is recommended to install PINN, which is an enhanced version of the NOOBS operating system installer.
Once installed, the system comes with SSH and VNC, no need to connect a keyboard and mouse to the Raspberry Pi, and you can debug it remotely.
△ Successfully connected to Raspberry Pi via VNC
Select to install Raspbian Lite from the many operating system options in PINN. After that, disconnect VNC and connect to the Raspberry Pi entirely via SSH.
The Raspberry Pi system comes with FTP, and to facilitate beginners in transferring files between the computer and Raspberry Pi, it is recommended to install FileZilla software.
Input the Raspberry Pi’s IP address, username, password, port 22, and click Quickconnect to connect to the Raspberry Pi’s file system. Now, you can drag and drop files from SpotMicroAI as needed.
Next is the most critical step, installing the robot dog control software. To simplify the installation, the author has written a script that automates the installation process:
ssh [email protected] https://gitlab.com/custom_robots/spotmicroai/basic-runtime/-/raw/master/utilities/self_install.sh | bashThen start the communication bus I2C. Open the terminal and run the following command:
sudo raspi-configThen make the following changes from the display options: Interfacing options → Enable I2C
Next, connect all the hardware to the Raspberry Pi as shown in the following image:
The 3D printing files for the robot dog’s shell are also included, and the author recommends using a 0.6mm nozzle with a layer height set to 0.3mm to maximize printing speed.
After assembling the hardware, the next step is software debugging.
First, download the default configuration file in JSON format: https : //gitlab.com/custom_robots/spotmicroai/basic-runtime/-//blob/master/spotmicroai.default and place it in the user’s home directory.
Open the calibration tool and calibrate the 12 servos to find the initial position of the motors when the robot dog is “resting”.
cd ~/spotmicroai/calibration./calibration.sh
After calibration, the robot dog can perform various actions.
Wait, what is the display screen installed at the back of the robot dog for? It actually helps us quickly see the current status of the robot dog.
For example, in the panel above, we can see the current temperature of the Raspberry Pi CPU, the connection status with the external controller, the status of the servo control board, and so on.
Thus, the mini robot dog is complete. If you not only want to assemble it but also learn more advanced development tutorials, you can check the content in Extra.
Next Steps
Currently, Mike’s mini robot dog can only perform some simple actions. Mike’s next plan is to make it as smart as the Boston Dynamics robot dog. Mike’s future goals are:
1. Add a laser radar to achieve simple 2D mapping of rooms through SLAM, just like the original Boston Dynamics robot dog.
Someone has already achieved Mike’s first goal:
2. Develop an automatic movement module to guide the robot to perform simple tasks around the sensed 2D environment, such as navigating in a room and avoiding obstacles.
3. Create software modules that combine cameras or webcams for basic image classification. For example, perceiving the closing and opening of a fist, allowing the robot to respond to a specific action and achieve gesture control.
Netizens: Let’s do it
DIYing the “Boston Dynamics dog” has received praise even from the Raspberry Pi official.
Netizens have expressed: This is really cool.
Some are eager to start making it themselves.
So, let’s do it?
Reference links:
https://www.raspberrypi.org/blog/mini-raspberry-pi-boston-dynamics-inspired-robot/
https://github.com/mike4192/spotMicro#Overview
https://gitlab.com/custom_robots/spotmicroai
Reprinted from the public account Quantum Bit
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