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avp_teleoperate

Unitree Robotics

English | 中文 | 日本語

📺 Video Demo

Watch the video

0. 📖 Introduction

This repository implements teleoperation of the Unitree humanoid robot using Apple Vision Pro.

Here are the robots that will be supported,

🤖 Robot ⚪ Status 📝 Remarks
G1 (29DoF) + Dex3-1 ✅ Completed
H1 (Arm 4DoF) ⏱ In Progress Refer to this branch's ik temporarily
H1_2 (Arm 7DoF) + Inspire ✅ Completed Refer to this branch
··· ··· ···

Here are the required devices and wiring diagram,

Watch the Document

1. 📦 Prerequisites

We tested our code on Ubuntu 20.04 and Ubuntu 22.04, other operating systems may be configured differently.

For more information, you can refer to Official Documentation and OpenTeleVision.

1.1 🦾 inverse kinematics

unitree@Host:~$ conda create -n tv python=3.8
unitree@Host:~$ conda activate tv
# If you use `pip install`, Make sure pinocchio version is 3.1.0
(tv) unitree@Host:~$ conda install pinocchio -c conda-forge
(tv) unitree@Host:~$ pip install meshcat
(tv) unitree@Host:~$ pip install casadi

p.s. All identifiers in front of the command are meant for prompting: Which device and directory the command should be executed on.

In the Ubuntu system's ~/.bashrc file, the default configuration is: PS1='${debian_chroot:+($debian_chroot)}\u@\h:\w\$ '

Taking the command (tv) unitree@Host:~$ pip install meshcat as an example:

  • (tv) Indicates the shell is in the conda environment named tv.
  • unitree@Host:~ Shows the user \u unitree is logged into the device \h Host, with the current working directory \w as $HOME.
  • $ shows the current shell is Bash (for non-root users).
  • pip install meshcat is the command unitree wants to execute on Host.

You can refer to Harley Hahn's Guide to Unix and Linux and Conda User Guide to learn more.

1.2 🕹️ unitree_sdk2_python

# Install unitree_sdk2_python.
(tv) unitree@Host:~$ git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
(tv) unitree@Host:~$ cd unitree_sdk2_python
(tv) unitree@Host:~$ pip install -e .

2. ⚙️ TeleVision and Apple Vision Pro configuration

2.1 📥 basic

(tv) unitree@Host:~$ cd ~
(tv) unitree@Host:~$ git clone https://github.com/unitreerobotics/avp_teleoperate.git 
(tv) unitree@Host:~$ cd ~/avp_teleoperate
(tv) unitree@Host:~$ pip install -r requirements.txt

2.2 🔌 Local streaming

Apple does not allow WebXR on non-https connections. To test the application locally, we need to create a self-signed certificate and install it on the client. You need a ubuntu machine and a router. Connect the Apple Vision Pro and the ubuntu Host machine to the same router.

  1. install mkcert: https://github.com/FiloSottile/mkcert
  2. check Host machine local ip address:
(tv) unitree@Host:~/avp_teleoperate$ ifconfig | grep inet

Suppose the local ip address of the Host machine is 192.168.123.2

p.s. You can use ifconfig command to check your Host machine ip address.

  1. create certificate:
(tv) unitree@Host:~/avp_teleoperate$ mkcert -install && mkcert -cert-file cert.pem -key-file key.pem 192.168.123.2 localhost 127.0.0.1

place the generated cert.pem and key.pem files in teleop

(tv) unitree@Host:~/avp_teleoperate$ cp cert.pem key.pem ~/avp_teleoperate/teleop/
  1. open firewall on server:
(tv) unitree@Host:~/avp_teleoperate$ sudo ufw allow 8012
  1. install ca-certificates on Apple Vision Pro:
(tv) unitree@Host:~/avp_teleoperate$ mkcert -CAROOT

Copy the rootCA.pem via AirDrop to Apple Vision Pro and install it.

Settings > General > About > Certificate Trust Settings. Under "Enable full trust for root certificates", turn on trust for the certificate.

Settings > Apps > Safari > Advanced > Feature Flags > Enable WebXR Related Features.

2.3 🔎 Test environment

This step is to verify that the environment is installed correctly.

  1. Download Isaac Gym: https://developer.nvidia.com/isaac-gym/download

    Extracting to the current directory, go to the IsaacGym_Preview_4_Package/isaacgym/python directory and execute the command:

    (tv) unitree@Host:~/IsaacGym_Preview_4_Package/isaacgym/python$ pip install -e .
  2. After setup up streaming with local following the above instructions, you can try teleoperating two robot hands in Issac Gym:

    (tv) unitree@Host:~/avp_teleoperate$ cd teleop
    (tv) unitree@Host:~/avp_teleoperate/teleop$ python teleop_test_gym.py
  3. Wear your Apple Vision Pro device.

  4. Open Safari on Apple Vision Pro and visit: https://192.168.123.2:8012?ws=wss://192.168.123.2:8012

    p.s. This IP address should match the IP address of your Host machine.

  5. Click Enter VR and Allow to start the VR session.

  6. See your hands in 3D!

3. 🚀 Usage

Please read the Official Documentation at least once before starting this program.

3.1 🖼️ Image Server

Copy image_server.py in the avp_teleoperate/teleop/image_server directory to the Development Computing Unit PC2 of Unitree Robot (G1/H1/H1_2/etc.), and execute the following command in the PC2:

# p.s.1 You can transfer image_server.py to PC2 via the scp command and then use ssh to remotely login to PC2 to execute it.
# p.s.2 The image transfer program is currently configured for binocular rgb cameras.

# Now located in Unitree Robot PC2 terminal
unitree@PC2:~/image_server$ python image_server.py
# You can see the terminal output as follows:
# Image server has started, waiting for client connections...
# Image Resolution: width is 640, height is 480

After image service is started, you can use image_client.py in the Host terminal to test whether the communication is successful:

(tv) unitree@Host:~/avp_teleoperate/teleop/image_server$ python image_client.py

3.2 ✋ Inspire hands Server (optional)

Note: If the selected robot configuration does not use the Inspire dexterous hand, please ignore this section.

You can refer to Dexterous Hand Development to configure related environments and compile control programs. First, use this URL to download the dexterous hand control interface program. Copy it to PC2 of Unitree robots.

On Unitree robot's PC2, execute command:

unitree@PC2:~$ sudo apt install libboost-all-dev libspdlog-dev
# Build project
unitree@PC2:~$ cd h1_inspire_service & mkdir build & cd build
unitree@PC2:~/h1_inspire_service/build$ cmake .. -DCMAKE_BUILD_TYPE=Release
unitree@PC2:~/h1_inspire_service/build$ make
# Terminal 1. Run h1 inspire hand service
unitree@PC2:~/h1_inspire_service/build$ sudo ./inspire_hand -s /dev/ttyUSB0
# Terminal 2. Run example
unitree@PC2:~/h1_inspire_service/build$ ./h1_hand_example

If two hands open and close continuously, it indicates success. Once successful, close the ./h1_hand_example program in Terminal 2.

3.3 🚀 Start

Warning

  1. Everyone must keep a safe distance from the robot to prevent any potential danger!

  2. Please make sure to read the Official Documentation at least once before running this program.

  3. Always make sure that the robot has entered debug mode (L2+R2) to stop the motion control program, this will avoid potential command conflict problems.

It's best to have two operators to run this program, referred to as Operator A and Operator B.

Now, Operator B execute the following command on Host machine :

(tv) unitree@Host:~/avp_teleoperate/teleop$ python teleop_hand_and_arm.py --record

And then, Operator A

  1. Wear your Apple Vision Pro device.

  2. Open Safari on Apple Vision Pro and visit : https://192.168.123.2:8012?ws=wss://192.168.123.2:8012

    p.s. This IP address should match the IP address of your Host machine.

  3. Click Enter VR and Allow to start the VR session.

When host terminal outputs "Please enter the start signal (enter 'r' to start the subsequent program):", Operator B can start teleoperation program by pressing the r key in the terminal.

At this time, Operator A can remotely control the robot's arms and dexterous hands.

Next, Operator B can press s key to begin recording data in the 'record image' window that opens, and press s again to stop. This can be repeated as necessary.

p.s. Recorded data is stored in avp_teleoperate/teleop/data by default, with usage instructions at this repo: unitree_IL_lerobot.

3.4 🔚 Exit

To exit the program, Operator B can press the q key in the 'record image' window.

Warning

To avoid damaging the robot, it's best to ensure that Operator A positions the robot's arms in a naturally lowered or appropriate position before Operator B presses q to exit.

4. 🗺️ Codebase Tutorial

avp_teleoperate/
│
├── assets                    [Storage of robot URDF-related files]
│
├── teleop
│   ├── image_server
│   │     ├── image_client.py [Used to receive image data from the robot image server]
│   │     ├── image_server.py [Capture images from cameras and send via network (Running on robot's on-board computer)]
│   │
│   ├── open_television
│   │      ├── television.py    [Using Vuer to capture wrist and hand data from apple vision pro]  
│   │      ├── tv_wrapper.py    [Post-processing of captured data]
│   │
│   ├── robot_control
│   │      ├── robot_arm_ik.py        [Inverse kinematics of the arm]  
│   │      ├── robot_arm.py           [Control dual arm joints and lock the others]
│   │      ├── robot_hand_inspire.py  [Control inspire hand joints]
│   │      ├── robot_hand_unitree.py  [Control unitree hand joints]
│   │
│   ├── utils
│   │      ├── episode_writer.py          [Used to record data for imitation learning]  
│   │      ├── mat_tool.py                [Some small math tools]
│   │      ├── weighted_moving_filter.py  [For filtering joint data]
│   │
│   │──teleop_hand_and_arm.py   [Startup execution code for teleoperation]
|   |——teleop_test_gym.py       [Can be used to verify that the environment is installed correctly]

5. 🛠️ Hardware

5.1 📋 List

Item Quantity Link Remarks
Unitree Robot G1 1 https://www.unitree.com/g1 With development computing unit
Apple Vision Pro 1 https://www.apple.com/apple-vision-pro/
Router 1
User PC 1 Recommended graphics card performance at RTX 4080 and above
Head Stereo Camera 1 [For reference only] http://e.tb.cn/h.TaZxgkpfWkNCakg?tk=KKz03Kyu04u For head
Head Camera Mount 1 https://github.com/unitreerobotics/avp_teleoperate/blob/g1/hardware/head_stereo_camera_mount.STEP For mounting head stereo camera, FOV 130°
Intel RealSense D405 2 https://www.intelrealsense.com/depth-camera-d405/ For wrist
Wrist Ring Mount 2 https://github.com/unitreerobotics/avp_teleoperate/blob/g1/hardware/wrist_ring_mount.STEP Used with wrist camera mount
Left Wrist Camera Mount 1 https://github.com/unitreerobotics/avp_teleoperate/blob/g1/hardware/left_wrist_D405_camera_mount.STEP For mounting left wrist RealSense D405 camera
Right Wrist Camera Mount 1 https://github.com/unitreerobotics/avp_teleoperate/blob/g1/hardware/right_wrist_D405_camera_mount.STEP For mounting right wrist RealSense D405 camera
M3 hex nuts 4 [For reference only] https://a.co/d/1opqtOr For Wrist fastener
M3x12 screws 4 [For reference only] https://amzn.asia/d/aU9NHSf For wrist fastener
M3x6 screws 4 [For reference only] https://amzn.asia/d/0nEz5dJ For wrist fastener
M4x14 screws 2 [For reference only] https://amzn.asia/d/cfta55x For head fastener
M2x4 self-tapping screws 4 [For reference only] https://amzn.asia/d/1msRa5B For head fastener

Note: The bolded items are essential equipment for teleoperation tasks, while the other items are optional equipment for recording datasets.

5.2 🔨 Installation diagram

Item Simulation Real
Head

head

Head Mount

head

Side View of Assembly

head

Front View of Assembly

Wrist

wrist

Wrist Ring and Camera Mount

wrist

Left Hand Assembly

wrist

Right Hand Assembly

Note: The wrist ring mount should align with the seam of the robot's wrist, as shown by the red circle in the image.

6. 🙏 Acknowledgement

This code builds upon following open-source code-bases. Please visit the URLs to see the respective LICENSES:

  1. https://github.com/OpenTeleVision/TeleVision
  2. https://github.com/dexsuite/dex-retargeting
  3. https://github.com/vuer-ai/vuer
  4. https://github.com/stack-of-tasks/pinocchio
  5. https://github.com/casadi/casadi
  6. https://github.com/meshcat-dev/meshcat-python
  7. https://github.com/zeromq/pyzmq
  8. https://github.com/unitreerobotics/unitree_dds_wrapper
  9. https://github.com/tonyzhaozh/act
  10. https://github.com/facebookresearch/detr
  11. https://github.com/Dingry/BunnyVisionPro