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Teleoperation of the Unitree H1_2 Humanoid Robot Using Apple Vision Pro

At SmilingRobo, we are thrilled to introduce a new open-source tutorial provided by Unitree Robotics that showcases the use of Apple Vision Pro for teleoperating the Unitree H1_2 humanoid robot. This exciting project demonstrates how cutting-edge augmented reality (AR) technology can be combined with robotics to create intuitive and efficient control systems for humanoid robots.

Overview

With this project, developers can simply wear the Apple Vision Pro headset and use gesture tracking through its built-in camera to control the humanoid robot in real time. This seamless integration of AR with robotics is a significant advancement, making it easier to control complex systems through natural human gestures.

Why This Matters

The ability to teleoperate robots through gesture tracking opens up endless possibilities for applications in remote operations, telepresence, and human-robot interaction. Whether you are managing tasks in industrial environments or remotely controlling robots for medical or research purposes, this combination of Vision Pro and Unitree’s robot offers immense potential.

This open-source tutorial is an excellent starting point for developers looking to integrate Vision Pro with robotic systems, allowing for immersive and hands-free control.

System Requirements and Prerequisites

To follow along with this tutorial and implement the teleoperation system, here are the prerequisites:

• Operating System: The code has been tested on Ubuntu 20.04 and Ubuntu 22.04. While the routine works on these versions, configurations may vary if you’re using a different OS.
• Software Libraries: You will need to configure several libraries to enable the robot’s inverse kinematics and motion control.

Environmental Dependencies

This teleoperation routine has been tested and confirmed to work on Ubuntu 20.04 and Ubuntu 22.04. If you are running a different operating system, you may need to adjust the build process to suit your environment.

• Pinocchio and CasADi: These libraries are used for inverse kinematics, specifically solving for the motor angle values of the humanoid robot’s arms (14 degrees of freedom). Pinocchio helps load the robot’s URDF (Unified Robot Description Format) and perform the necessary calculations to convert gestures into motor movements.

• Apple Vision Pro Integration: Vision Pro tracks the left and right wrist poses of the user, transmitting this data to the robot for real-time motion control. When the user moves their arms, the Vision Pro headset detects the pose and translates it into robot arm movements through inverse kinematics.

• Meshcat: This library is used to visualize the robot’s movements during debugging. It provides a 3D representation of the robot’s kinematic model, helping developers ensure that the robot’s movements align with the user’s gestures.

双臂 Inverse Kinematics Environment Setup

For precise control of the Unitree H1_2’s dual-arm system, an inverse kinematics environment must be set up. The process involves:

1. Wrist Pose Tracking: The Vision Pro headset captures the poses of both wrists.
2. Inverse Kinematics Calculation: The captured data is fed into the Pinocchio and CasADi libraries, which calculate the motor angles needed to move the robot’s arms into the desired positions.
3. Visualization: Meshcat is employed to visually debug and ensure accuracy.

This process enables precise manipulation of the robot’s 14 degrees of freedom, making the robot capable of mimicking human arm movements in real-time.

Why This Is a Game-Changer

The use of Apple Vision Pro for teleoperation not only simplifies robotic control but also makes it far more intuitive. By leveraging AR and advanced gesture tracking, users can control robots without needing complex remote controls or coding skills. This breakthrough opens up opportunities for developers and industries alike to explore new ways to interact with robots.

The combination of open-source resources with state-of-the-art hardware like Vision Pro paves the way for exciting developments in fields such as:

• Telepresence: Users can control robots in remote environments, making it possible to complete tasks in hazardous or hard-to-reach locations.
• Medical Applications: Surgeons and medical professionals could potentially operate robots to assist in delicate procedures or deliver medical supplies.
• Research and Development: Scientists and engineers can control robots for experimentation in environments where human presence is not feasible.

Conclusion

This project is a fantastic starting point for any developer interested in combining robotics with augmented reality. With Apple Vision Pro.