Humanoid robot Unitree G1 Edu Flagship E-U7

Unitree G1 Edu Flagship E-U7 Humanoid Robot for AI Research and Development

Unitree G1 Edu Flagship E-U7 is a humanoid robot designed for scientific research, education, artificial intelligence algorithm development, and human-robot interaction experiments, with 41 degrees of freedom, a computational NVIDIA Jetson Orin NX 16GB module, and two five-fingered Revo 2 Basic hands. The model supports secondary development and works with ROS2 and SDK2 tools, allowing for real-time programming of movements, navigation, and object interaction. It is equipped with an Intel RealSense D435i camera, 3D LiDAR, and each hand can hold and carry loads weighing up to 3 kg.

Advantages and Features of Unitree G1 Edu Flagship E-U7

• Degrees of freedom and humanoid kinematics. The Unitree G1 Edu Flagship E-U7 humanoid robot has 41 degrees of freedom and supports expansion up to 43 in the maximum configuration. Large joint motion angles of the arms, legs, and body enable complex manipulations, balancing, and movement in research project conditions.
• Humanoid Revo 2 Basic hands. The flagship version is equipped with two humanoid hands with position and force control support. The manipulators can work with fragile objects and lift loads weighing up to 3 kg.
• High computational power. The onboard NVIDIA Jetson Orin NX 16GB module with over 100 TOPS is optimized for computer vision processing, imitation learning, and reinforcement learning methods. It works with multimodal AI models UnifoLM.
• Comprehensive spatial perception. A 360° panoramic view is provided by the proprietary Unitree 4D LiDAR-L1, Intel RealSense D435i depth camera, and an additional 3D LiDAR for navigation and 3D SLAM. A 4-microphone array is responsible for command recognition. This allows for building three-dimensional maps of the room, recognizing obstacles, and working with voice commands.
• Flexible programming. Full low- and high-level control over the drives through unitree_sdk2 (C++/Python) is open. The robot is fully compatible with ROS2 and has ready-made URDF digital models for simulation in Gazebo and Isaac Sim, simplifying algorithm testing before launching on real equipment.
• Reliable power mechanics. Knee drives develop a torque of up to 120 Nm, and industrial roller bearings are designed for long-term operation. A removable 9000 mAh battery provides up to 2 hours of autonomous operation, and the foldable body of 690x450x300 mm facilitates transportation between laboratories and educational centers.
• Official extended warranty. The Edu series robotic complex comes with an official 18-month warranty, providing full technical support and service.

Design and Hardware

The robotic platform has a stable architecture with a height of 1320 mm and a total weight of about 35 kg, designed for long-term experiments and intensive dynamic loads. The knee joints are equipped with high-efficiency permanent magnet motors (PMSM) with low inertia, generating a torque of up to 120 Nm for instant body stabilization, running, or overcoming obstacles.

Large deviation angles of the pelvic, knee, and waist joints allow for complex movement scenarios not available to most other humanoid platforms. All moving joints of the mechanism are equipped with industrial cross-roller bearings for high positioning accuracy. The cable wiring is routed in a hidden manner inside the hollow frame elements, fully protecting the communication lines from mechanical wear. An important engineering advantage is the presence of a built-in 5W speaker in the head, which, together with the microphone array, provides full-fledged two-way voice communication. For convenient transportation between laboratories or auditoriums, the body folds to compact dimensions — 690×450×300 mm.

Precise Object Handling with Robotic Hands

The flagship configuration of the Unitree G1 Edu Flagship E-U7 is equipped with two full-fledged humanoid manipulators with 5 fingers on each hand, whose design is close to human body kinematics. The main feature of the Revo 2 Basic hands is the integrated hybrid control of joint force and position, allowing the device to accurately calculate the interaction force with the environment. This enables the robot to delicately handle objects of various geometric shapes, densities, fragility of glassware, and tools.

The anatomical structure of the manipulators supports data collection on pressing force and material resistance in real-time, helping researchers work out precise gripping scenarios. Each hand's load capacity is up to 3 kg, fully covering the needs of most research, logistics, and educational tasks involving object movement.

Control Systems and Computational Resources

For engineers and developers, the Unitree G1 Edu Flagship E-U7 offers full low-level and high-level control over the drives and sensors through the open unitree_sdk2 interface in C++ and Python programming languages. Full integration with the ROS2 operating system simplifies the connection of third-party software modules and plugins. The availability of detailed URDF digital models allows for accurate simulation of the humanoid's physical behavior in virtual environments like Gazebo and NVIDIA Isaac Sim before testing algorithms on real hardware.

Standardized holes on the robot's back are provided for securely attaching additional equipment. For connecting third-party sensors and payloads, power lines of different voltages are output at 12V, 24V, and 58V, as well as high-speed engineering interfaces: Gigabit Ethernet RJ45 ports, USB-C, and industrial buses GPIO, I²C, and UART.

Sensors for Navigation and Object Recognition

Spatial orientation and map building in three-dimensional space are based on a complex combination of modern machine vision sensors. The robot's head integrates the proprietary Unitree 4D LiDAR-L1, which performs 21,600 laser scans per second, providing ultra-precise scanning of the surrounding environment without blind spots.

The perception system is complemented by the Intel RealSense D435i depth RGB-D camera and an additional long-range 3D LiDAR. This hybrid sensor array allows the robot to build 3D maps using SLAM technology without delays, recognize objects on the path, and dynamically avoid obstacles. A 4-microphone array is responsible for receiving and analyzing acoustic information, enabling precise localization of the sound source in the room and recognizing user voice commands.

Platform for Machine Learning and Autonomous Systems

The main computational node of the Unitree G1 Edu Flagship E-U7 is the onboard computer based on the NVIDIA Jetson Orin NX module with a capacity of 16 GB. With computational power exceeding 100 TOPS, the platform is ideally optimized for local processing of heavy neural networks and computer vision algorithms directly on the robot.

The model supports advanced machine learning methods — imitation learning (based on operator actions) and reinforcement learning. Software capabilities and motion patterns are regularly updated via wireless OTA packages. The hardware is fully adapted for local work with large multimodal artificial intelligence models UnifoLM. This allows programming completely autonomous robot behavior, recognizing complex sequential engineering commands, and interacting with people without the need for constant connection to cloud servers.

Applications

Unitree G1 Edu Flagship E-U7 is designed for scientific and educational projects. The platform allows for experiments with autonomous mobility, low-level drive control, and manipulator management in the following areas:

• Scientific research and R&D: development of artificial intelligence algorithms, testing reinforcement learning methods, and modeling human-machine interaction.
• Navigation and spatial perception: research on autonomous navigation, computer vision, building three-dimensional room maps, and SLAM algorithms.
• Manipulation and motion control: practicing delicate object handling, testing walking patterns, and dynamic motion control algorithms.
• Education and applied use: teaching students robotics and mechatronics, conducting university laboratory projects, and designing service robots.

Compatibility with Educational Platforms

Unitree G1 Edu Flagship E-U7 is adapted for use in universities, research laboratories, and educational centers. The open architecture simplifies integration with additional equipment and software complexes.

The humanoid robot supports work with:

• ROS 2;
• Python;
• C++;
• NVIDIA JetPack;
• external cameras;
• additional LiDAR sensors;
• laboratory data collection systems;
• research machine learning platforms;
• network Ethernet devices;
• GPIO modules and peripheral equipment.

Thanks to standardized connection interfaces, the platform easily adapts to various scientific and educational projects. The availability of technical documentation and developer tools allows for quickly starting work on your own research tasks.

Unitree G1 Edu Flagship E-U7 Package

The device comes assembled and ready for initial launch after unpacking. The basic package includes all necessary elements for autonomous power and wireless control.

1. Unitree G1 Edu Flagship E-U7 humanoid robot.
2. Quick-release lithium battery with a capacity of 9000 mAh.
3. Network charger with parameters 54 V, 5 A.
4. Wireless handheld control remote.
5. User manual and technical passport.

Technical Specifications of Unitree G1 EDU

Usage Tips

• Power control. Before each launch, be sure to check the battery charge level to avoid sudden shutdown of the robot during movements.
• Surface preparation. Use only a flat, dry, and non-slippery surface for practicing walking algorithms, stabilization, and balancing.
• System updates. Regularly update software and motion skill packages through official wireless tools (OTA) from Unitree.
• Development ecosystem. For creating your own algorithms, simulations, and secondary development, it is recommended to use official ROS2 and unitree_sdk2 environments.

Warnings and Safety

• Startup without support. Do not power on the Unitree G1 Edu when it is lying on the ground or in an unstable position without support. Initial startup and calibration should only occur on a protective hanging stand or special chair.
• Rough battery installation. Avoid forcing the battery into the fuselage with excessive physical force. If the block does not smoothly slide into the slots until it clicks, stop the process immediately to avoid damaging the internal power connectors.
• Programming without Debug mode. Do not send your own commands through the SDK without first switching the robot to development mode (L2 + R2). Ignoring this rule causes a severe conflict with the built-in motion controller, leading to strong jitter and drive failure.
• Overloading. Do not load the Revo 2 Basic robotic hands with more than 3 kg. Overloading will lead to critical overheating of the servos and failure of the gearboxes.
• Hot sensor connection. Connecting or disconnecting third-party sensors and expansion modules to the GPIO, I²C, UART interfaces on the robot's back is prohibited when the system is on and voltage is applied to the ports. All manipulations with the payload are performed only on a de-energized device.

Buy Unitree G1 Edu Flagship E-U7

Order the Unitree G1 Edu Flagship E-U7 for universities, research centers, laboratories, and companies working in the field of robotics, research, and development of artificial intelligence systems. We will help you choose the optimal configuration for your tasks, provide technical consultation, and ensure complete documentation of the order.