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Unitree G1-Comp (RoboCup) Humanoid Football Robot
Regular price
€0,00
Unitree G1-Comp (RoboCup) is a humanoid robot designed for football competitions. It uses motion control systems, visual recognition, spatial positioning, and motion control APIs to operate in competitive match environments. The robot supports simulation training to real robot deployment through the unitree_rl_gym reinforcement learning framework. It is compatible with the ROS ecosystem and supports Isaac Gym and Mujoco simulation environments.
Highlights
- Designed for RoboCup-style football competitions.
- Uses a YOLO11-based visual recognition algorithm for real-time target detection and stadium environment identification.
- Provides spatial positioning through monocular geometric positioning and binocular depth positioning.
- Includes motion control APIs for decision systems based on visual detection results, venue information, and competition rules.
- Supports high-level and low-level operation control interfaces, status service interface, DDS communication interface, and audio lighting service interface.
- Supports Isaac Gym and Mujoco simulation environments.
- Compatible with the ROS ecosystem.
- Development computing unit uses Jetson Orin NX with 100 TOPS AI computing power.
- Battery life is about 2 hours and supports quick change and fast charging.
Technical specifications
| Spec | Value |
| Model | G1 Comp |
| Height, width and thickness, standing | 1320 x 450 x 200 mm |
| Height, width and thickness, folded | 690 x 450 x 300 mm |
| Weight with battery | About 35 kg+ |
| Calf + thigh length | 0.6 m |
| Arm span | About 0.45 m |
| Total degrees of freedom | 25-45 joint degrees of freedom |
| Single leg degrees of freedom | 6 |
| Waist degrees of freedom | 1 + optional 2 additional waist degrees of freedom |
| Single arm degrees of freedom | 5 |
| Head degrees of freedom | 2 |
| Single hand degrees of freedom | 7, optional force control of three-fingered hand, plus optional 2 additional wrist degrees of freedom |
| Dex3-1 thumb active degrees of freedom | 3 |
| Dex3-1 index finger active degrees of freedom | 2 |
| Dex3-1 middle finger active degrees of freedom | 2 |
| Dex3-1 tactile sensor arrays | Optional |
| Maximum torque of knee joint | 120 N.m |
| Arm maximum load | About 3 kg |
| Waist joint | Z ±155°, X ±45°, Y ±30 |
| Knee joint | 0~165° |
| Hip joint | P ±154°, R -30~+170°, Y ±158° |
| Wrist joint | P ±92.5°, Y ±92.5° |
| Full joint hollow electrical routing | Yes |
| Joint encoder | Dual encoder |
| Cooling system | Local air cooling |
| Power supply | 13 string lithium battery |
| Basic computing power | 8-core high-performance CPU |
| Development computing unit | Jetson Orin NX |
| AI computing power | 100 TOPS |
| Sensing sensor | Depth camera, 3D LiDAR |
| Microphone array | 4 microphone array |
| Speaker | 5 W speaker |
| WiFi 6 | Yes |
| Bluetooth 5.2 | Yes |
| Battery capacity | 9000 mAh smart battery, quick release |
| Battery life | About 2 h |
| Charger | 54 V 5 A |
| RoboCup SDK visual recognition API | Built-in YOLO11 latest generation real-time target detection algorithm |
| RoboCup SDK spatial positioning API | Monocular geometric positioning and binocular depth positioning |
| RoboCup SDK motion control API | Motion control interfaces for the decision system based on visual detection results, venue information, and competition rules |
| Operation control interfaces | High-level operation control interface, low-level operation control interface |
| Service and communication interfaces | Status service interface, DDS communication interface, audio lighting service interface |
| Simulation environments | Isaac Gym, Mujoco |
| Large model | UnifoLM Large Model |
| TTS and ASR | Supported |
| YOLO recognition algorithm | Supported |
| ROS support | Compatible with ROS ecosystem |
| APP support | Quickly configure robots and view status |
| Upgraded intelligent OTA | Yes |
| Secondary development | Yes |
| Shell | Covered with aluminum alloy and high-strength engineering plastics |
Use cases
- RoboCup football competitions
- Competitive match environments
- Stadium environment recognition and positioning
- Simulation training using Isaac Gym or Mujoco
- Sim2Sim to Sim2Real robot deployment
- ROS ecosystem development
- Secondary development
What's in the box
- High computing power module: NVIDIA Jetson Orin
- Smart battery, quick release, 9000 mAh
- Charger, 54 V 5 A
- Manual controller