Core Specifications
The H2 Edu is a human-scale platform designed to operate in environments built for people.
| Feature | Specification |
| Height | 182 cm (~6 ft) |
| Weight | ~70 kg (including battery) |
| Degrees of Freedom (DOF) | 31 (Head: 2, Waist: 3, Arms: 7×2, Legs: 6×2) |
| Max Torque | Leg joints: 360 Nm / Arm joints: 120 Nm |
| Computing Power | 2,070 TOPS (supports NVIDIA Jetson AGX Thor) |
| Battery Life | ~2–3 hours (quick-replaceable 0.972 kWh battery) |
| Connectivity | WiFi 6, Bluetooth 5.2 |
Key Features & Innovations
1. Advanced Articulation & Movement
The H2 Edu features a major hardware overhaul compared to the H1. It includes a 3-DOF serial waist and a 2-DOF articulated neck, allowing it to yaw and pitch its head for dynamic perception. This enables the robot to track objects or people without rotating its entire torso, making it significantly more “lifelike.”
2. High-Precision Actuation
Utilizing Unitree’s proprietary high-torque motors and a “quasi-serial” tendon-driven system in the legs, the H2 Edu achieves low inertia.10 This allows it to perform complex, high-impact movements—such as martial arts kicks, backflips, and 360-degree spinning kicks—while maintaining perfect stability upon landing.
3. “Edu” Open Development Platform
Unlike the consumer version, the Edu edition is built for secondary development:
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Full SDK Access: Supports C/C++ and Python for custom motion control and AI algorithms.
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Sensor Integration: Equipped with dual-eye binocular cameras and 3D LiDAR for 360-degree environmental awareness.
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Simulation-Ready: Designed to be “RL-friendly” (Reinforcement Learning), making it easier to train behaviors in digital twins and deploy them to the physical robot.
4. Human-Centric Design
The H2 features a bionic face with defined features (eyes, nose, lips) and is designed to wear human clothing.16 This makes it an ideal platform for social robotics research, where the robot’s appearance and non-verbal communication are critical for user acceptance.
Targeted Applications
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Advanced Robotics Research: Exploring bipedal locomotion, balance control, and collision response.
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AI & Machine Learning: Serving as a physical host for Large Language Models (LLMs) and computer vision research.
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Service & Logistics: Testing object manipulation, sorting, and navigation in human-centric workspaces.











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