Core Components

High-Resolution Camera Arrays

Capture real-time images of the field, covering every inch as the robot moves.

Often include RGB and infrared cameras for better contrast between crops and weeds.

Computer Vision + AI/ML Models

Pre-trained deep learning models (e.g., convolutional neural networks) identify plant species at the leaf level.

The system distinguishes between crops and weeds with ~95%+ accuracy, even in dense planting environments.‍

‍Precision Laser System

Typically uses high-energy CO₂ or fiber lasers (around 150W–300W).

Mounted on robotic gantries or articulated arms to aim at individual weeds.

Delivers short bursts of intense heat (over 1000°C) to rupture plant cells and kill the meristem, the growing point of the weed.

Real-Time Targeting System

‍ Based on GPS + inertial navigation for macro location and robotic micro-adjustments for laser targeting.
Laser firing is triggered only when the system is confident in weed classification.

Autonomous Navigation‍

The machine moves through rows using GPS, LiDAR, or RTK guidance, operating day or night.

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