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Robots can be broadly divided into three categories: industrial robots, service robots, and special robots. Although the market size of special robots is relatively smaller than the other two, with the accelerated evolution of new technological and industrial transformations, the deep integration of 5G, artificial intelligence, and robotics technology has expanded the application scenarios for special robots. They are increasingly playing a crucial role in various industries. This article will introduce a special robot, namely intelligent inspection robot, whose function is to replace manual inspection and maintenance of equipment. Additionally, we will explore the main functions of the intelligent inspection robot and introduce the FET3588J-C SoM recommended by Forlinx Embedded as the main control platform for the robot. In the process of rapid urban development, more and more pipelines are laid underground. How to maintain such a large area of underground pipe gallery quickly and accurately? Considering the complex and potentially hazardous environment of underground tunnels, the underground space intelligent inspection robot emerges. Intelligent robot inspection and monitoring systems, as well as disposal systems, can be installed in underground tunnels to construct a smart operation and maintenance software platform. This platform enables regular detection and monitoring of the basic attributes within the space, ensuring the normal operation of the facilities. Intelligent inspection robots are generally divided into three main parts: the robot operation, the IoT sensing, and the application. They are respectively used for “ensuring the normal operation of the robot,” “perceiving the underground space,” and “processing and responding to the data collected by the IoT sensing part.” (1) Real-time Detection and Environmental Monitoring The robotic system can monitor the site environment in real-time through the high-definition camera. It can collect information such as humidity, temperature, and harmful gas concentration at the equipment site through external temperature and humidity sensors, which is then uploaded to the cloud via 4G or 5G. (2) Fully Automatic Inspection According to its own time settings or remote control from the cloud, the inspection robot can perform routine tasks and specialized training inspections through real-time GPS and 5G positioning of its location. (3) Automatic Charging and Automatic Return at Low Power It can independently judge the state of battery power, automatically return when the battery power is insufficient, and cooperate with the charging equipment to complete the autonomous charging; (4) Autonomous Obstacle Avoidance Function During the monitoring process, the robot incorporates NPU machine vision to recognize and differentiate track obstacles and pipeline obstacles from the camera-collected data. It can immediately stop and upload alarm information. (5) Automatic Generation of Inspection and Monitoring Reports It organizes the information collected from this inspection and produces an inspection and monitoring report of the site status after CPU simplified processing to visualize the site data. Forlinx Embedded has launched the FET3588J-C core board as the main control platform for this intelligent inspection robot product to meet customers' needs for machine vision and high-speed interfaces. The FET3588J-C is developed and designed based on the Rockchip RK3588 processor. It features quad-core Cortex A76+quad-core Cortex-A55 architecture, with the main frequency of A76 core up to 2.4 GHz, and the main frequency of A55 core up to 1.8 GHz, which enables efficient processing of the collected information from inspections. Built-in Rockchip self-developed three-core NPU can work cooperatively or independently, so as to flexibly allocate computing power and avoid redundancy. The comprehensive computing power can reach 6 TOPS, which greatly improves the computing speed and energy efficiency ratio of neural network, and can better realize the function of active obstacle avoidance; The RK3588J supports 48 million pixels ISP 3.0, which enables lens shading correction, 2D/3D noise reduction, sharpening and defogging, fisheye correction, gamma correction, wide dynamic contrast enhancement, and other effects that greatly enhance image quality. It also offers high stability and can operate for long periods in harsh industrial environments ranging from -40°C to +85°C, making it suitable for applications in various scenarios. In addition, it also supports Linux 5.10, 66/Android 12 high-version and high-stability operating system, with more perfect driver and open system source code, so that customers can quickly enter the product testing stage. Originally published at www.forlinx.net.

The Forlinx OKMX8MP-C development board is equipped with two native CAN buses. However, in certain product development scenarios, there is a need for additional CAN buses. This article will introduce a method for SPI to CAN conversion, providing engineers with a reference. Description • The FETMX8MP-C SoM has two native SPI buses. Currently, the pins of SPI1 are being used for LED and UART3 functions, while SPI2 is configured as a normal SPI2 interface. Taking SPI2 to CAN conversion as an example, the process involves porting the SPI to CAN chip; • The model of the SPI to CAN chip is MCP2518. This chip is capable of converting to CAN-FD. If only CAN functionality is required, you can refer to this method for porting MCP2515 or other chips; • The driver for the MCP2518 chip in this porting process is sourced from the i.MX8MQ's firmware code. The MCP2518 chip is already ported by default in the processor. 1. Porting the MCP2518 chip driver Create a folder named "mcp25xxfd" under the path "OK8MP-linux-kernel/drivers/net/can/spi/". Place the relevant files (including .c files, .h files, Makefile, Kconfig, etc.) in this folder. 2. Complete the definition of can _ rx _ offload _ add _ manual function. vi OK8MQ-linux-kernel/include/linux/can/rx-offload.h Add: int can_rx_offload_add_manual(struct net_device *dev, struct can_rx_offload *offload, unsigned int weight) vi OK8MQ-linux-kernel/drivers/net/can/rx-offload.c Add: int can_rx_offload_add_manual(struct net_device *dev, struct can_rx_offload *offload, unsigned int weight) { if (offload->mailbox_read) return -EINVAL; return can_rx_offload_init_queue(dev, offload, weight); } EXPORT_SYMBOL_GPL(can_rx_offload_add_manual); 3. Modify Makefile and Kconfig under the previous directory SPI/ vi OK8MP-linux-kernel/drivers/net/can/spi/Makefile Add: obj-y += mcp25xxfd/ vi OK8MP-linux-kernel/drivers/net/can/spi/Kconfig Add: source "drivers/net/can/spi/mcp25xxfd/Kconfig" 4. Modify the driver configuration file and compile the MCP2518 into the kernel vi OK8MP-linux-kernel/arch/arm64/configs/OK8MP-C_defconfig Get：CONFIG_CAN_MCP251X=y Change to：# CONFIG_CAN_MCP251X is not set Add：CONFIG_CAN_MCP25XXFD=y 5. Configure the clock in the device tree vi OK8MP-linux-kernel/arch/arm64/boot/dts/freescale/OK8MP-C.dts Add: clocks{ mcp2518fd_clock: mcp2518fd_clock{ compatible = "fixed-clock"; #clock-cells =; clock-frequency =; }; }; 6. Find a pin to use as the interrupt pin of the chip GPIOUNK1IO21 is used as an interrupt pin here. vi OK8MP-linux-kernel/arch/arm64/boot/dts/freescale/OK8MP-C.dts Add: pinctrl_ecspi2_can: ecspi2can{ fsl,pins = < MX8MP_IOMUXC_SAI2_RXFS__GPIO4_IO21 0x40000 >; }; 7. Modify in the ecspi2 node of the device tree vi OK8MP-linux-kernel/arch/arm64/boot/dts/freescale/OK8MP-C.dts From： &ecspi2{ #address-cells=; #size-cells=; fsl,spi-num-chipselects=; pinctrl-names= "default"; pinctrl-0= <&pinctrl_ecspi2 &pinctrl_ecspi2_cs>; cs-gpios= <&gpio5 13 GPIO_ACTIVE_LOW>; status= "okay"; spidev1:spi@0 { reg=; compatible= "rohm,dh2228fv"; spi-max-frequency=; }; }; Change to： &ecspi2{ #address-cells=; #size-cells=; fsl,spi-num-chipselects=; pinctrl-names= "default"; pinctrl-0= <&pinctrl_ecspi2 &pinctrl_ecspi2_cs &pinctrl_ecspi2_can>; cs-gpios= <&gpio5 13 GPIO_ACTIVE_LOW>; status= "okay"; mcp1:mcp2518fd@0{ compatible= "microchip,mcp2518fd"; reg=; spi-max-frequency=; clocks= <&mcp2518fd_clock2>; interrupts-extended= <&gpio4 21 IRQ_TYPE_LEVEL_LOW>; }; }; After completing the above modifications, you can compile and burn the OKMX8MP-C development board with the newly generated image. Connect the MCP2518 chip to the SPI2 interface, start the OKMX8MP-C development board, and then use the ifconfig -a command to view it, and you can see that there is one more CAN node. Originally published at www.forlinx.net.

Automated Guided Vehicles (AGV), also known as unmanned transport vehicles, are characterized by their significant feature of unmanned driving. AGVs are equipped with an automatic guidance system, which ensures that the system can automatically travel along a predetermined route without the need for manual guidance. They can transport goods or materials automatically from the starting point to the destination. Depending on the navigation method, AGVs can be divided into various types, such as electromagnetic navigation AGVs, laser navigation AGVs, magnetic strip navigation AGVs, QR code navigation AGVs, and vision navigation AGVs. Among various forms, visual navigation products are the most capable of applying AI technology. They can dynamically capture the surrounding environment image information through cameras, compare it with the stored images database, and after repeated comparisons, they can engage in deep learning to determine the current state and make decisions for the next steps of travel. Key Features: Automated Navigation: Through autonomous navigation technologies such as laser navigation, visual navigation, and magnetic navigation, robots can independently plan paths, avoid obstacles, and perform tasks. Precision and Safety: It can operate on highly accurate paths to perform material handling and distribution tasks, reducing human errors and safety risks. Multiple Payload Capacities: It can be designed and configured to accommodate different sizes and weights of goods or materials based on requirements. Flexibility: Adaptability to different manufacturing and warehousing environments. It can easily adapt to different production and warehouse environments, allowing for adjustments in tasks and paths based on requirements. Reduction of Labor Costs: The application of AGV can reduce manual labor and lower labor costs. Improving Efficiency: Compared with traditional labor, it can greatly improve the efficiency of production and logistics. The ARM architecture has several notable advantages in AGV (Automated Guided Vehicle), making it one of the widely adopted processor architectures. Here are the key benefits of ARM in AGVs: Low Power Consumption: The ARM processor architecture is known for its low-power characteristics, which is important for AGVs, which often need to run for long periods of time without interruption to perform material handling and distribution tasks. High Performance: ARM processors offer a wide range of performance levels, from low-power embedded cores to high-performance multi-core processors, which can be selected according to the AGV's application requirements for efficient task execution. Multi-core Support: The ARM architecture supports multi-core processor designs, which is beneficial for AGV applications that require parallel processing and complex calculations. Rich Ecosystems: ARM is supported by a rich set of development tools, compilers, operating systems and software libraries, which make it easier to develop and deploy AGV applications. Customizable: The ARM architecture allows hardware designers to customize the processor to meet the performance, power and size requirements of AGV applications based on specific needs. Wide Range of Applications: ARM processors are widely used in a variety of applications, including embedded systems, mobile devices, IoT and automation, making it easier to access technical support and resources for adopting the ARM architecture in AGVs. Cost-effectiveness: ARM processors are typically less expensive for cost-sensitive applications such as AGVs. The Forlinx FET3568-C SoM is developed based on the Rockchip RK3568 processor, featuring a quad-core 64-bit Cortex-A55 architecture with a high frequency of up to 2.0GHz. This processor is a domestic application platform created by Rockchip specifically for the AIoT and industrial markets, offering high performance, low power consumption, and rich functionality. AGV Application Advantages： Powerful performance, combining GPU, NPU, and VPU in one. Built-in NPU with 1TOPS arithmetic power to meet the demand for lightweight AI computing in the application process, supporting Caffe / TensorFlow / TF-Lite / ONNX / PyTorch / Keras / Darknet mainstream architectures, bringing convenience to machine learning. Rich interface functionality, convenient for peripheral expansion, including 2 CAN FD interfaces, 4 independent USB interfaces (supporting up to USB 3.0), 3 SATA 3.0 controllers, and 2 built-in GMACs with support for RGMII/SGMII/QSGMII (2 MAC) interfaces, enabling dual gigabit Ethernet. Support 1080p60fps H.264 and H.265 format hardware encoding; support dynamic bit rate, frame rate, and resolution adjustment. The board has been subjected to severe ambient temperature tests, pressure tests, and long-term stability operation tests to ensure that it works stably and reliably. Originally published at www.forlinx.net.

An embedded Single Board Computer is a complete circuit board that integrates a processor, memory, interfaces, clocks, and other auxiliary circuits. It is commonly used to create embedded systems, such as those used for controlling robots, automobiles, or industrial equipment. Here is an introduction to embedded Single Board Computers and some tips on how to use and choose the right one: 01 What is an Embedded Single Board Computer? A Single Board Computer is a circuit board used for developing embedded systems. It includes a central processing unit (CPU), memory, input devices, output devices, data pathways/buses, and external resource interfaces, among other hardware components. It serves as a platform for cooperation within the semiconductor industry, providing manufacturers with essential low-level hardware, system, and driver resources. This eliminates the need for users to invest manpower and time to complete these low-level tasks. Common types of Single Board Computers include 51, ARM, FPGA, and DSP. Forlinx is dedicated to the development and service of ARM architecture Single Board Computers. Single Board Computers, in concept, are very similar to software outsourcing. In terms of embedded products, the hardware, boot code, drivers, file systems, protocol layers, and basic application software are considered common and generic components of electronic products. They do not encompass the key technologies that differentiate the product. In this era that emphasizes division of labor and cooperation, if the workload in this area is significant or if a manufacturer lacks relevant development personnel, they can choose to outsource these development tasks to a third-party. This accelerates the product development process and enables quick time-to-market, seizing a competitive advantage. Forlinx Embedded Single Board Computer integrates all the core functional circuits commonly found in embedded products. It combines the processor with RAM, Flash memory, power management, LCD, Ethernet, USB, and other universal interfaces into a compact, reliable, and electromagnetic-compatible electronic motherboard. By adopting a SoM for product development, you can avoid complex processor development, BGA design, high-speed PCB routing, design verification, EMC compliance design, as well as save the effort required for extensive board debugging and BSP (Board Support Package) development work. When selecting a Single Board Computer, you are actually choosing not just a hardware board and the resources it provides, such as source code, but also choosing a partner, a collaborator who provides software and hardware services to users. Similar to the cooperation model of software outsourcing, the collaboration between users and suppliers in this case is primarily focused on software cooperation. It requires thorough communication between the user and the supplier to understand the specific requirements of the product. The supplier needs to continuously allocate personnel according to the user's needs to ensure effective collaboration. During the process of supporting customers in product development, Forlinx often encounters issues such as modifying the file system, serial port testing, upgrading Flash memory from 64MB to 128MB, etc. In most cases, these issues need to be resolved through software solutions. This forms a high level of interaction between embedded industry suppliers and customers in terms of after-sales support and customer development. In other words, embedded Single Board Computers serve as the medium for user's software outsourcing. Compared to traditional software outsourcing, Single Board Computers actually provide users with value in terms of both hardware and software services. 02 How to Use an Embedded Single Board Computer? Using an embedded Single Board Computer requires some knowledge of hardware and software. Here are a few steps to help you get better at using embedded Single Board Computers: 1. Understand the specifications and features of the Single Board Computer, read relevant documentation and manuals, or study relevant tutorials. 2. Familiarize yourself with the programming language and IDE environment you will use. 3. Write code, connect hardware, debug the program, and validate the results. This includes tasks such as GPIO control, PWM waveform output, serial communication, and short message transmission. 03 How to Choose an Embedded Single Board Computer? Choosing the right embedded Single Board Computer can greatly improve development efficiency. Here are some factors to consider when purchasing an embedded Single Board Computer: 1. Processing power: Consider the specification and performance of the board’s processor to ensure it can handle your application’s requirements. ARM Cortex series should be given priority consideration because they have extensive support and ecosystem. 2. Interfaces and expand-ability: It is important to determine which peripherals need to be added based on your project requirements. Check if the Single Board Computer has relevant general-purpose input/output (GPIO) and expansion interfaces. It is also beneficial to consider the compatibility with operating systems and network connectivity components. 3. Cost: This can be an important factor for budget-conscious projects, but it's important not to focus solely on price. Quality should be a priority consideration. You can also explore options such as using older models that have already been released, which may help reduce costs. 4. Support and maintenance: Look for a reliable supplier or manufacturer that offers timely technical support and maintenance services. Having a strong support team can definitely help you solve problems and overcome challenges. 5. Estimated life-cycle: Consider the life-cycle of the Single Board Computer. Choosing a product with long-term support is indeed crucial to ensure ongoing support and availability of replacements in the future. 6. Hardware and Software Ecosystem: Consider the ecosystem of the Single Board Computer, including development tools, documentation, community support, and third-party software and hardware support. Indeed, a strong ecosystem can greatly reduce development time and difficulty. 7. User feedback and reviews: Look for user feedback and reviews about the Single Board Computer to understand the experiences and suggestions of other developers. Searching for user feedback and reviews about the Single Board Computer to understand the experiences and suggestions of other developers. In general, choosing an embedded Single Board Computer requires considering multiple factors such as performance, interfaces, ecosystem, cost, and support. Exactly, it's important to choose the Single Board Computer that suits your application's specific requirements and goals. This ensures that the chosen board is well-suited for the intended purpose. Embedded Single Board Computers serve as the medium for user's software outsourcing. Compared to traditional software outsourcing, Single Board Computers actually provide users with value in terms of both hardware and software services. More Embedded Single Board Computer Originally published at www.forlinx.net.

Looking for a single board computer that can meet the requirements of various scenarios such as industrial control, intelligent healthcare, environmental monitoring, transportation, power, renewable energy, and security surveillance? Look no further than the Forlinx Embedded OK-MX9352-C single board computer! With its meticulous protection design and adherence to ISO9001 quality management system, it ensures secure and stable communication for all your needs. More info: https://www.forlinx.net/article_view_493.html

In this article, we will introduce the SoMs of the Allwinner series. Allwinner × Forlinx Embedded The cooperation between Forlinx Embedded and Allwinner Technology started in 2019. Up to now, Forlinx Embedded has launched 3 SoMs based on Allwinner processors--FETT507-C, FETA40i-C, and FETT3-C that won unanimous recognition of the market. 01 Allwinner T507 Series FETT507-C SoM is designed and developed based on Allwinner T507 quad-core industrial level processor Cortex-A53 with main frequency 1.5GHz, integrated with G31 GPU, 2GB DDR3L RAM, and 8GB eMMC storage. With Linux, Android, and Forlinx Desktop operating systems, it is suitable for in-vehicle electronics, power, medical care, industrial control, IoT, intelligent terminals, and other fields. 02 Allwinner A40i Series The FETA40i-C SoM is designed based on Allwinner industrial control level processor quad-core Cortex-A7 A40i with main frequency 1.2GHz, integrated with MAli400MP2 GPU, 1GB/2GB DDR3L RAM, 8GB eMMC storage. It supports most current popular video and image formats decoding and has the advantages of stable and reliable industrial-level product performance, cost-effective and low-power consumption, etc. Equipped with Linux and Android operating systems, it is suitable for industrial control products based on visual interaction. 03 Allwinner T3 Series FETT3-C SoM is designed and developed based on Allwinner quad-core car navigation processor Cortex-A7 with main frequency 1.2GHz, integrated with MAli400MP2 GPU, 1GB DDR3L RAM, 8GB eMMC storage. Entire board industrial level running temperature supports most current popular video and image formats decoding and has the advantages of stable and reliable industrial-level product performance, low-power consumption, rich interfaces etc. Equipped with Linux and Android operating systems, it is suitable for in-vehicle electronics, power, medical care, industrial control, IoT, intelligent terminals, and other fields. Above is the big list of Forlinx Embedded’s Allwinner series; the industrial-level quality makes the application more stable and reliable.

In recent years, RISC-V has attracted a lot of attention because of its completely open source, free of charge, and free to modify without constraints. Under this background, Forlinx Embedded works together with a RISC-V processor manufacturer and launches FET7110-C SoM based on Jinghong(JH) 7110 processor! The FET-JH7110-C SoM is designed and developed based on the JH7110 processor, with a process of 28 nm, open source RISC-V architecture, main frequency of 1.5 GHz, and integrated 4-core U74 architecture; It has powerful GPU processing capability and supports multi-lane video encoding and decoding, common functional interfaces such as 2xPCIe 2.0, 2xGigabit Ethernet, 2xCAN 2.0, etc. The SoM supports Linux 5.15.0 suitable for industrial vision-related application development. In the future, Forlinx Embedded will take an active and open attitude in continuing to cooperate with more chip manufacturers and provide customers with more stable, reliable, and comprehensive intelligent control products! Other Recommended Articles: RISC-V | High-Performance FET7110-C SoM Is Coming Soon!

In this article, we will introduce the SoMs of the Rockchip. Rockchip x Forlinx Since 2020, Forlinx Embedded has launched three SoM products based on Rockchip RK3399, RK3568, and RK3588 processors and got affirmation and recognition from thousands of enterprise users. 01 RK3588 Series The FET3588J-C SoM is developed and designed based on the Rockchip new generation flagship RK3588J processor, which adopts an advanced 8nm process and integrates quad-core Cortex-A76 + quad-core Cortex-A55, with A76 cores frequency up to 1.6GHz and A55 cores frequency up to 1.3GHz, providing powerful performance support. It supports an 8K ultra-high-definition display and a four-screen heterodyne display, and it is equipped with a wealth of high-speed data communication interfaces to meet the diverse needs of users. After rigorous test, it can operate stably for a long time under -40~+85℃. 02 RK3568 Series FET3568J-C SoM is developed and designed based on Rockchip RK3568J processor, which integrates quad-core 64-bit Cortex-A55 architecture, with frequency up to 1.8GHz and built-in NPU. It is a high-performance, low-power, feature-rich application processor built by Rockchip for the AIoT and industrial markets. The FET3568J-C SoM has been subjected to industrial-grade standard ambient temperature tests, pressure tests, and long-term stability operation tests to ensure its stable and reliable operation. 03 RK3399 Series FET3399-C SoM is the first product jointly launched by Forlinx Embedded and Rockchip. It is based on Rockchip's RK3399 processor design and has two ARM Cortex-A72 cores at 1.8GHz and four ARM Cortex-A53 cores at 1.4GHz; the GPU adopts Mali-T864 and supports OpenGL ES1.1/2.0/3.0/3.1, OpenVG1.1, OpenCL, DX11; 2GB LPDDR3 RAM on board (4GB optional), 16GB eMMC ROM. With its powerful performance configuration, this SoM has been widely used in cutting-edge technology fields such as intelligent self-service terminals, edge computing, 5G intelligent terminals, visual recognition, etc.

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Introducing the FETMX6ULL-S System on Module (SoM) based on the powerful i.MX6ULL processor! This highly adaptable SoM features a dual native Ethernet ports, dual CAN controller, and octa UART, making it the perfect choice for a wide range of applications in various embedded systems and domains. With its compact size of 44*35mm, the FETMX6ULL-S SoM offers a perfect balance between performance and space efficiency. Whether you're working on media playing, digital camera integration, or WXGA display projects, this SoM has got you covered! Not only does it support 24-bit parallel LCD output up to WXGA (1366x768) for crystal-clear visuals, but it also boasts features like a 8/10/16/24-bit parallel camera sensor OV9650, three IIS interfaces, and ALSA audio form for an immersive multimedia experience. The FETMX6ULL-S SoM comes in both industrial-grade and expansion commerce-grade options, catering to various project requirements. Choose from 256MB DDR3L/512MB DDR3L RAM and 256MB NandFlash/4GB eMMC storage options to suit your needs. Rest assured, this SoM is well-supported with Linux 4.1.15 and QTGUI, ensuring a seamless development experience. With support for OTG, SD/TF card flashing mode, and separate kernel updates, you have the flexibility to customize and optimize your projects effortlessly.

It's honored for Forlinx for the witness and interaction with NXP for the the announcement of i.MX91 SoC a new promising applications processor. As NXP's Gold Partner, Forlinx has kept close touch and communication with NXP since the initial programming of the i.MX91 SoC. As NXP's newest highlight SoC, it's introduced that the i.MX91 SoC delivers an optimized blend of the security, scalability, features, and performance required to enable the next generation of long-life, cost-optimized, and flexible Linux controller platforms for IoT and Industrial applications. ‘i.MX 91 Family X Ecosystem = IoT’ quoted by Robert Thompson the Director of Secure Connected Edge Ecosystem at NXP Semiconductors. We do believe that the premiere of i.MX91 SoC will broaden more users with advanced, cost-optimized and high-security solutions. Here we are pleased to introduce and take you all have a forward-looking at the features of the upcoming i.MX91 based SoM FET-MX91xx-C.

FET3588-C System on Module (SoM) carries Rockchip’s advanced hybrid processor RK3588 contains quad-core Cortex-A76 and Cortex-A55 cores, A76 core runs up to 2.4GHz, and A55 core clock up to 1.8GHz. It has a super advanced engine can support up to 8K output, quad-screen with different content output; The SoM has been subjected to rigorous ambient temperature testing, which approves that it could be a trusted and best option for your high-end applications and products. Feature of Rockchip RK3588 8K video codec, can support various codec forms; ISP3.0 up to 48MP; Various video outputs up to 8K@60Hz; 4 PCIe3.0 and 3 PCIe2.1, up to 8Gbps; Multiple USB3.1 Type-C can support SATA3.1;

The Forlinx RK3588 evaluation kit integrates an embedded Mali G610 3D GPU with support for OpenGLES 1.1, 2.0, 3.2, OpenCL 2.2, and Vulkan 1.2. The special 2D hardware engine with MMU can maximize display performance and provide very smooth operation. In this article, we will test the performance of the GPU performance.