With the development of network technology and grid computing, “ubiquitous computing” centered on embedded mobile devices will become a reality. From the traditional industrial robot used for production and processing to the modern entertainment robot which enriches the public life, it is inseparable from the embedded system. But what we often talk about is the software and hardware system with microcontroller as the core.

Hardware: low power consumption, good tailoring, high real-time (rich interrupts), small size, rich interface and peripheral resources, some can be parallel computing and so on. In terms of software: fast operation speed, basic FPU floating-point operation system, real-time operating system (VxWorks, μ cos, FreeRTOS, μ Clinux… At present, there are some open-source real-time operating systems in China, such as RT thread, GUI, etc.

Almost all robots and intelligent devices will use embedded devices, such as MCU, arm, FPGA, DSP, ASIC and so on. At present, the fire of embedded system seems to be spreading in the Internet and artificial intelligence industry. This trend and current situation are related to the good adaptability of the two fields, and of course, to the promotion of arm architecture and various EDA tools. Even at present, embedded artificial intelligence has developed into a new concept in the industry, which opens up an important branch in the AI field.

What are the advantages of embedded technology in logistics robot industry

AI technology and algorithm are finally implemented on local embedded devices to realize local real-time environment recognition and perception, human-computer interaction, decision-making control and so on. Embedded artificial intelligence is a breakthrough of computing marginalization away from the cloud. With the increasing AI requirements of mobile devices, many computing will migrate from data center to mobile devices to realize embedded edge computing.

AI plus embedded devices are used in various industries and fields. The most popular image recognition and voice interaction technology is used in various mobile terminals. The popular concepts and attempts include automatic driving (after all, there is no mature market), virtual reality, etc. The more common ones are UAV, multi axis manipulator, deep vision recognition equipment and AGV in logistics warehousing and automation Chemical production industry application.

The intelligent warehouse, which is composed of warehouse logistics robot, makes the heavy work in storage simple and fast, saves human resources and improves work efficiency. Fixed multi axis industrial manipulator robot, combined with the use of depth vision camera to detect materials, mixed destacking operation of roller assembly line. Intelligent handling robot is used to carry out automatic material handling operation, mainly including knapsack type, lifting type and roller type.

Forklift AGV, different from the traditional manual forklift, can carry out automatic driving, automatic stacking and other tasks. It can accurately locate and fork goods, and realize machine to machine, machine to ground, ground to ground, and stacking pallet and other modes. Intelligent bin picking robot, highly flexible goods to person robot, suitable for different height of goods location, realize automatic lifting, grabbing and handling work, so as to realize storage automation.

Logistics robot hardware is generally composed of several modules: power module, motor drive module, sensor module (infrared sensor, ultrasonic sensor, vibration sensor, camera, depth camera and lidar sensor), processor, display, loudspeaker module, etc. These modules together constitute the embedded hardware system, which provides the basis for the robot to realize various functions.

The main work of the embedded processor of logistics robot generally includes: one is used to run the robot system, the other is to collect sensor data, or the two are combined into one, using an embedded chip to process the robot system and sensor data.

The performance of the current embedded chip running robot system may be slightly worse than that of the x86 architecture chip, but the general task is enough, and even the special embedded AI chip can accelerate the data processing of the system. The popular robot operating system ROS (very good robot learning platform) is responsible for the operation of the entire robot task, sensor data reading, slam, navigation, object recognition, speech recognition, robot arm motion planning and Internet connection, etc.

     

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