FET3588J-C CPU Board: High-performance Engine for Intelligent AI Weeding Robot

Traditional weed removal methods include manual weeding, mechanical weeding, physical weeding, chemical weeding, etc. However, these methods are either inefficient with high labor costs, or they fail to completely remove weeds, leading to environmental pollution and residual chemical substances that can be absorbed by the soil, thereby affecting subsequent plant production.

Excessive use of herbicides, with glyphosate being the main component, poses significant risks as it can enter the bodies of animals through contaminated food and water. The use of mechanical weeding can disrupt soil structure and ecological balance. On the other hand, manual weeding is time-consuming, laborious, and costly.

In recent years, there has been a growing demand for intelligent living, and with the maturity of machine vision technology, cameras can be used to capture images and identify weeds, enabling selective weed removal. As a result, the use of herbicides can be reduced or eliminated. In the field of agriculture, smart weeding robots are gradually emerging as a promising solution.

The most crucial step in the crop and weed detection process for a weeding robot is accurately differentiating between crop plants and weeds. It is indeed not an easy task to differentiate between crops and weeds due to the wide variety and irregular distribution of weeds, as well as the similarities in physical characteristics between crops and weeds.

If we want an artificial intelligence system to determine whether to remove an object (weed) from the ground, it needs more than just the ability to recognize the object optically. It also needs the capability to differentiate whether the object is a weed or a crop.

Weeds and crops typically have different spectral characteristics, which is why multi-spectral cameras can help in accurately classifying them by ensuring that the optical sensors capture images that enable proper differentiation. This capability can assist the system in successfully removing weeds.

Features of smart weeding robots include:

Efficient intelligence: Equipped with advanced image recognition technology, smart weeding robots can accurately identify weeds and crops, achieving precise weeding operations and improving work efficiency.

Autonomous navigation: Equipped with advanced navigation systems, smart weeding robots can autonomously plan work paths, adapt to different shapes and sizes of farmland, and provide comprehensive coverage to ensure thorough weed removal.

Environmentally friendly and efficient: Powered by batteries, zero emissions, environmentally friendly. By adopting intelligent weeding technologies such as lasers, the use of chemical herbicides is reduced, resulting in lower residue levels in agricultural products.

Autonomous decision-making and learning: Algorithms with autonomous decision-making capabilities enable robots to respond adaptively to new situations. Machine learning techniques can be used to improve recognition and decision-making capabilities.

To better meet the high-performance requirements of intelligent weeding robots, Forlinx Embedded has launched FET3588J-C platform, which has the following characteristics:

High performance and low power consumption: The FET3588J-C quad-core Cortex-A76 runs at up to 2.4GHz to support high-load operation, while the quad-core Cortex-A55 is suitable for low-power operation at low-load operation, balancing performance and power efficiency.

Advanced image processing: The FET3588J-C introduces a new generation of 48-megapixel ISP3.0, which enables lens shading correction, 2D/3D noise reduction, sharpening and de-fogging, fisheye correction, gamma correction, and wide dynamic contrast enhancement, which dramatically improves the quality of robotic image capture.

Rich interface resources: It has abundant interface resources to meet the access needs of robots to various sensors. More access to sensors helps devices to more fully capture environmental data. The platform can also access external storage interfaces such as SATA3.0 and USB3.0 so that data can be stored locally, and it also supports wireless communication methods such as WiFi, 4G, and 5G, which makes it convenient for users to query device information on the mobile side. The rich functions enable the robot to perceive and understand the surrounding environment more comprehensively.

Powerful AI computing power: It has a built-in NPU with a computing power of 6 TOPS, which provides powerful AI learning and edge computing capabilities for robots to cope with different work scenarios more intelligently.

Extreme stability and performance support: The SoM of the platform has undergone rigorous environmental temperature testing and stress testing, providing extreme performance support and stable operation guarantee for high-end applications, ensuring that the intelligent weeding robot can perform well in various complex environments.

With the continuous upgrading of intelligent hardware, intelligent weeding robot has become an important technology in modern agriculture. As its core engine, Forlinx's Embedded FET3588J-C platform provides more powerful support for the development of intelligent weeding robots, and brings more efficient and intelligent solutions for weeding robots.

Originally published at www.forlinx.net.

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