Developer Solution Kits Propel Robotic Production

With a surge of interest in the robotics market, production can’t keep up. A new development kit is making it easier to integrate artificial intelligence and machine vision into robots and test designs before creating prototypes. The result is less costly development and faster time to market.


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Image source: Cogniteam


Robotic technology is on the rise. Fueling the growth of smart robots is innovation in robotic technology, the increasing need for autonomous robots in the workplace, and demand for robots enabled with artificial intelligence (AI). The smart robot market is forecasted to reach $14.3 billion by the year 2023. With this projected increase, large manufacturers are looking for cost-effective methods to reduce production time and incorporate contactless, efficient solutions into their manufacturing processes. New developer kits are proving to be the answer.

From Virtual Testing to Field Testing 

AAEON, in collaboration with Intel and Amazon Web Services (AWS), created the UP Squared RoboMaker Developer Kit to shorten the time between the virtual testing environment and having market-ready robots. The RoboMaker simplifies the development, simulation, testing, and deployment of intelligent robotics applications at scale, thus reducing production time. The kit is best suited for large-scale robot manufacturers. 

Featured in the RoboMaker Developer Kit is the UP Squared board with an Intel® Atom™ processor, Intel® Movidius™ Myriad™ X VPU, Intel® RealSense™ Camera, and the Intel® Distribution of the OpenVINO™ toolkit. The Intel processors, vision accelerators, and cameras make it easy for developers to add AI capabilities to their edge computing applications. The OpenVINO toolkit allows developers to add visual intelligence to robotics and prevents hardware from overheating by managing the allocation of resources between CPU/GPU and VPU. 

Tutorials provide instructions for building the hardware from the module level and explain how to use cloud-based services to shorten development time. The kits do not include unique robotic parts, such as wheels, control boards, and motors.

UP Squared RoboMaker Developer Kit put to use

Image credit UP-Bo

The AWS RoboMaker enables developers to test their machine designs or prototypes in virtual scenarios. Developers run their code in a simulated environment and can tweak design flaws before building a prototype or manufacturing additional robots. This lessens the time to market and the cost of production, and is particularly valuable for developers who cannot access a physical robot for testing. 

Autonomous Robots for Industry 4.0

A wide range of industries utilize AI-integrated machines; from grocery stores to car manufacturers. The kit is optimal for creating autonomous mobile robots, warehouse robots, and retail robots, as those industries are pushing market demand. Manufacturing and the intelligent factories of Industry 4.0 will increasingly rely on autonomous robots, which enhance operational efficiency.

The kit allowed Israel-based Cogniteam to build an autonomous ATV robot from scratch in just one day. Cogniteam’s prototype, Lynx, is equipped with ROS interfaces, OpenVINO support, deep learning VPU, and is integrated with AI and self-learning capabilities. These technologies allow Lynx to complete autonomous maneuvers at up to 25 miles per hour. It is currently in beta testing.  

NexCOBOT, a NEXCOM company, created a robotic design with integrated AI and machine vision capabilities for use in automotive assembly lines. The NexCOBOT solution uses Intel® Celeron® processors and Intel® Core™ i7 processors, the Intel® OpenVINO™ toolkit to integrate AI, and the Intel® Movidius™ VPU for computer vision acceleration at the edge. EtherCAT-based robot control systems are built using the Intel® Ethernet Controller. 

Designed to ease operator workloads on automotive assembly lines, the NexCOBOT robot uses AI vision to take photos of a plate of LED modules and classify the modules. The robot can distinguish between the patterns, colors, and shapes of various LED modules and find them in different locations, which is critical as the arrangement of LED modules can frequently change. Based on the AI data, the robot can plug in and test each module as needed, preparing the assembly line. It is designed for low-volume, high-mix manufacturing. 

AAEON’s new robotic developer kits provide developers with a simpler way to add machine learning and vision to their edge computing applications. That allows developers to bring new levels of sophistication to their robotic offerings. 

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