With the continuous expansion of the service robot market, the demand for one smart module with functions such as data analysis, workload integration, artificial intelligence, 5G connectivity, and remote manageability is growing. Hence, Intel has launched the Intel® Smart Mobile Machine Reference Design, hoping to solve industry problems and create a standard that is easy to add new features and improve efficiency.
Resolve industry pain and create greater value for customers
The advancement of digital technology is changing the way of service provision of traditional self-service terminals to end users. It means that static and passive interactive self-service terminals are transforming into smart mobile terminals. For the robotics industry, computing modules not only need to provide computing power for complex navigation and operation, but also need additional computing power to support artificial intelligence workloads, media processing, and other related needs. However, robots vary in size and function which depend on the requirements of specific applications. Furthermore, each case requires a long cycle of design and verification.
Standardization is the trend, full coverage of requirements
In order to solve the industry’s pain, AmbiWork launched 3.5″ embedded board called “JUNO-U112”. The size is small and the standard 3.5-inch board saves space and facilitates the design of the whole machine. The structure adopts latest 11th Gen. Tiger Lake UP3 Platform that can provide high computing abilities and an expansion board to keep the flexibility of other add-in functions. Users can connect graphics cards, AI accelerator cards and motion control cards to meet high-end custom requirements such as visual recognition, AI processing and motion control. In addition, the speed and scalability of the CAN module provide users with more choices when choosing sensor modules. The board supports CPU configurations from Celeron to Core™ i7, and the AI computing power is doubled than previous generation CPU, which satisfies the computing performance requirements from motion control to vision algorithms.
