Introduction Technology

Autonomous driving and remote driving technologies

1. Core technology

Autonomous driving

-Environmental perception: GPS, LiDAR, cameras, millimeter-wave radar, etc., are used to identify terrain, crops and obstacles.

- Path planning: SLAM algorithm, AI decision-making system, optimize job paths.

- Control system: Electric/hydraulic actuator, precisely controlling steering, speed and operating tools.

Remote driving

- Low latency communication: 5G and satellite communication ensure real-time video transmission and control command issuance.

- Human-machine interaction interface: VR/ AR-assisted operation, multi-screen monitoring of agricultural machinery status and environment.

2. Application scenarios

Autonomous driving

-Sowing, fertilizing and harvesting in large-scale farmland.

-Drones precisely spray pesticides.

-24-hour continuous operation.

Remote driving

-Handling complex terrain or sudden obstacles (such as remote takeover for obstacle avoidance).

-High-risk environmental operations (such as pesticide spraying, fire monitoring).

-Multi-agricultural machinery collaborative scheduling (one control for multiple machines mode).

3. Advantages

1) Efficiency improvement

-Reduce reliance on human labor and extend working hours.

-Precise operation reduces the waste of seeds and fertilizers (such as variable fertilization techniques).

2) Enhanced security

-Remote operation reduces personnel exposure to harsh environments.

3) Flexibility

-Autonomous driving handles routine tasks, while remote driving responds to sudden demands.