The concept of Industry 4.0 is driving the popularity of private 5G networks, which are also increasingly being adopted in the manufacturing and logistics space due to falling spectrum costs, Renu Navale, Group Vice President Network and Edge and General Manager of the Edge Platforms Division of Intel Corporation, said during a presentation at the 5G Manufacturing Forum – available on demand here.
“So a number of Industry 4.0 use cases, around smart manufacturing, logistics, energy and warehouse automation utilities, smart grids, fault detection represent more 60% of our use cases for private 5G,” said the leader.
Navale said the warehouse automation market is expected to reach $27 billion by 2025. “And by 2025, there will be over 4 million robots in operation and approximately 50,000 automated distribution warehouses. So there will be a huge opportunity in our industrial ecosystem for Autonomous Mobile Robots (AMR). »
The Intel executive also pointed out that 5G sets a new paradigm for AMRs by driving distributed computing efficiency through its ultra-reliable, low-latency communications and high bandwidth capabilities.
“There’s a really nice cycle where edge computing is becoming more available and more popular. And that drives down the costs of AMRs, because the compute is more available closer to the source of the data generated from AMRs. And at the same time, even the cost of AMRs is becoming more affordable, with warehouses planning to deploy hundreds of these AMRs,” she said.
Navale said some of the automated warehouse tasks can be located on the AMRs, while some can be offloaded to the edge server. And then in some cases, some of the tasks may go to the data center or the cloud.
According to Intel, some of the tasks that can be localized on AMRs include sensor ingestion, trajectory planning and localization, obstacle avoidance, motor control, functional safety and navigation, while tasks that can be offloaded to the edge server include remote interference, fleet management, mission management, battery management, traffic management and analysis.
“And our vision is that for us to enable these compute and AI functions in AMRs, they really have to be based on latency and other requirements. And then there’s a logical distribution of these workloads on these different sites that can generate the best efficiencies as well as the best business value for businesses.
Explaining how Intel currently enables use cases using AMRs, Navale noted that the chipmaker “has a fairly diverse portfolio of processors and accelerators, including GPUs and network cards that can enable offerings. from device to cloud”.
“In addition to our silicone portfolio, we also have a significant amount of software offerings, which are used to enable these use cases with autonomous mobile robots,” added the leader.
“We really have three key offerings that are actually used in these AMR use cases. The first is called Edge Insights for AMR. This is our optimized software stack in AMR platforms that has various building blocks such as simultaneous localization and mapping, which is used to actually activate and control autonomous mobile robots,” she said. . The second software offering is Intel’s OpenVINO, which it described as its “toolbox with AI, computer vision, and deep learning inference.” This software accelerates visual inference for images captured by cameras located on robots. This is very critical for AMR navigation in factories, but also to ensure that AMRs operate safely and co-exist with humans in factories. Finally, our Intel Smart Edge offering, which is used to manage and deploy AMR applications,” added Navale.
Meanwhile, Walter Buga, CEO of Arendai, a San Diego-based startup that focuses on orchestrating and automating logistics centers and smart factories, said 80% of warehouses are not automated. and noted that many solutions aimed at automating warehouses operate as silo solutions.
He said that Arendai’s Harmony 1.0 is a software solution for automating logistics and warehouse operations, which enables the management of AMRs from different vendors, introduces expanded AI capabilities to AMRs using IT from cutting edge, implements a digital twin for predictive maintenance and operations optimization and creates a safe environment for RAMs and human collaboration.
The Harmony solution uses Intel Edge Insights for autonomous mobile robots on AMR platforms and IntelSmart Edge on edge platforms to deploy edge computing applications and global management and orchestration services for AMRs.
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