Drones
Unitree Go2 EDU
The Unitree GO2 EDU is a fully open-system robotic dog that takes programming and modification capabilities to a new level. With powerful hardware and modularity, you can connect custom sensors, modules, or program AI algorithms for exploration, rescue, or industrial applications.
Specification
Comparison of Go1 and Go2 parameters
| Parametry | Go1 | Go2 |
|---|---|---|
| Maximum speed | 5 m/s | 5 m/s |
| Weight | 12 kg | 15 kg |
| Payload | 5 kg for a long duration, short term 10 kg | 8 kg for a long duration, short term 12 kg |
| Obstacle sensor/cameras | Cameras front, bottom, left, right | LiDAR |
| Video transmission from cameras | Yes | Yes + LiDAR SLAM |
| Maximum battery life | 45 min | 4 h |
| Maximum ground tilt | 30 ° | 40 ° |
Recognition, modelling and autonomous navigation
The Unitree GO2 EDU revolutionizes spatial analysis with its integrated 4D LiDAR L1 that performs 360 ° × 90 ° scanning at 43,200 points per second. This system detects obstacles from a height of 5 cm up to a distance of 20 meters and produces detailed 3D maps in real time. The robot can autonomously plan routes in challenging terrain, be it forest cover, industrial rubble or crowded interiors, making it the ideal partner for search operations or exploration of unknown environments.
With 12 articulated motors that deliver up to 45 N.m of torque and a cooling system based on heat pipes, the GO2 EDU overcomes obstacles 16 cm high and climbs slopes up to 40 °. Its aluminium alloy construction and IP54 resistance allow it to operate in a temperature range from -10 °C to 50 °C.
Future in DronySIT
At DronySIT, we are developing our own control application that opens up new possibilities for rescue and reconnaissance projects. This intuitive interface, designed specifically for the needs of the IZS (integrated rescue system), combines ease of use with advanced features for remote collaboration.
With our app, the GO2 EDU can be controlled in real time – whether it’s for surveying collapsed buildings, search operations in forests or monitoring danger zones. Simply choose between automatic mode (where the robot autonomously maps the terrain and avoids obstacles) and manual control with live feed from the built-in camera. The key is the synergistic approach: while the GO2 EDU collects data, the operator analyzes the situation and decides on the next course of action.
In the future, the plan is to enrich the application with tools that push the boundaries of possibilities. We plan to integrate AI detection of people or the generation of optimized routes to search large areas. The screenshot shows the visual style of the app: a clean interface with a 3D terrain map, a robot status overview and live video. It’s a future where technology is not just for control, but for saving lives and solving challenges that are beyond human capabilities today.
