Intelligent Lawn Mowing Robot Main Control Solution Based on RK3576
With the rise of smart outdoor automation, intelligent lawn mowing robots are rapidly replacing traditional gasoline-powered mowers in Europe and America. To meet growing demands for autonomy, precision, and environmental performance, embedded system designers are turning to powerful platforms like the Rockchip RK3576. As a high-performance processor with built-in AI acceleration, the RK3576 offers an ideal main control solution for next-generation smart lawn mowers.
1. RK3576 SoM: A New and More Powerful Engine
The rising consumer demand for more functions in lawn mowing robots is creating an urgent need in the industry for intelligent and efficient technical solutions. As the core technological carrier of the intelligent wave, the Rockchip RK3576 processor, with its high-performance computing, high computing power, multi-sensor fusion, and low-power design, is expanding the technical boundaries of intelligent lawn mowing robots and driving the products to evolve towards greater precision, autonomy, and environmental friendliness.
The FET3576-C system on module(SoM) developed by Forlinx Embedded based on the Rockchip RK3576 chip uses advanced 8nm process technology. It integrates a quad-core Cortex-A72 (with a main frequency of 2.3GHz) and a quad-core Cortex-A53 (with a main frequency of 2.2GHz), and is equipped with a Mali-G52 MC3 graphics processing unit (GPU) and a neural network processing unit (NPU) with an independent computing power of 6TOPS, making it a more powerful engine for high-end lawn mowing robots.
2. Technological Innovation Driven by Powerful Performance
Using Forlinx Embedded's FET3576-C SoM, this powerful engine, as the main control device for the new-generation lawn mowing robots significantly enhances the functionality and performance. The technological innovation is mainly reflected in the following aspects:
(1) Core Computing Architecture
The FET3576-C SoM CPU features four Cortex-A72 cores and four Cortex-A53 cores. The big.LITTLE architecture enables it to support the concurrent execution of multiple tasks such as route planning, image acquisition, and mechanical control.
(2) AI Computing Acceleration System
The NPU built into the FET3576-C core board supports INT4/INT8/INT16/FP16/BF16/TF32 operations and multiple deep-learning frameworks like TensorFlow, Caffe, and Pytorch. With a computing power of 6TOPS, it can achieve accurate object recognition and detection, identify various obstacles in complex environments, and optimize lawn mowing route decisions.
(3) Realization of Intelligent Weeding System
The FET3576-C SoM constructs a complete functional closed-loop for intelligent mowing robots through diverse bus interfaces. Thanks to the FlexBus parallel bus (with a maximum clock of 100MHz and compatible with 2/4/8/16-bit transmission) and high-speed interfaces such as DSMC, CAN-FD, PCIe2.1, SATA3.0, and USB3.2, it can be flexibly adapted to multi-spectral camera arrays (connected via MIPI-CSI) and various actuators.
In terms of function realization, the AI vision algorithm uses camera data for accurate real-time obstacle identification; the decision-making layer uses AI models for dynamic path planning; the execution end controls the laser module or robotic arm through CAN/GPIO interfaces for millimeter-level precise operations. In addition, Wi-Fi and Bluetooth support remote setting of virtual boundaries and viewing of work logs via mobile phone apps.
3. Summary
Lawn mowing robots are transitioning from traditional tools to intelligent platforms, placing higher demands on the performance, stability, and AI capabilities of the main control system. The FET3576-C SoM, with its high-performance heterogeneous computing, powerful AI inference ability, and comprehensive system expansion interfaces, constructs an intelligent operation closed-loop from “perception-decision-execution”, providing solid technical support for intelligent lawn mowing robots and injecting more innovation impetus into the fields of smart homes and automated outdoor equipment.
