Automate Your Logistics Operations Using AMRs to Increase Productivity and Efficiency

By Rich Nass

Contributing Editor

Embedded Computing Design

March 26, 2021

Blog

Automate Your Logistics Operations Using AMRs to Increase Productivity and Efficiency
(Image courtesy of Pixabay)

The e-commerce and online retail industries are experiencing exponential growth, resulting in more stringent demands being placed on logistics operations worldwide. Logistics companies and their suppliers are relying on automation more than ever to increase productivity and efficiency.

Designing a full-blown logistics automation system can be somewhat unwieldy. Hence, dividing that system into smaller subsystems can make the design process more manageable. For example, you can break it down into order picking, storage, and goods conveyance and/or packaging. These functions would require multiple types of robots, controlled by vision and data-acquisition systems. And ideally, it’s all integrated seamlessly though one central secure hub.

Autonomous mobile robots (AMRs) can reduce operating expenses (OPEX) in the logistics automation environment, leveraging artificial intelligence (AI) to establish a lean supply chain and ensure accuracy. It all starts with the understanding that a warehouse is a dynamic environment, with constant change that may require workflow adjustments on the fly. In addition, regulations are continually updated, putting stress on system developers.

According to Amit Goel, Director of Product Management for Autonomous Machines at NVIDIA, “Integrating IoT edge computing and AI is a key part of this design. Customers can leverage the Jetson edge AI platform and application specific SDKs like Isaac to bring intelligence to these autonomous systems. Distributing this intelligence across the different components of a warehouse enables levels of autonomy and productivity, which isn’t possible with a single central compute infrastructure.”

Not Just Hardware

Note that it’s really the combination of hardware and software that results in the highest level of efficiency. To that end, NVIDIA is creating application-specific SDKs which enable developers to more easily develop solutions aimed at particular industries. And because it’s all running on the same core platform, the integration is streamlined. It’s also easier to monitor and update software when necessary.

For example, if you consider warehouse automation, the requirements could be as simple as scanning a product to check whether it's the right product in the right location. That could be done with an AI-enabled machine vision camera. At the other end of the spectrum, you may need an AMR with enough processing capability for moving throughout the warehouse autonomously,   ensuring that obstacles are avoided by making use of AI enabled perception while planning the most efficient path to reach its destination.

ADLINK Technology, one vendor prominent in the AMR space, including logistics automation, has now gained years of field knowledge that it deploys in its platforms. And most customers have different criteria that must be met, depending on a host of factors.

Sorting Through the Data

Note that a logistics system has the potential to generate a flood of operational data that needs to be sorted and acted upon in real time. Says Zane Tsai, Head of the Platform Product Center for the Embedded Platforms and Module Business Unit at ADLINK Technology, “Real-time is a difficult task. You have to have all your equipment talking to each other using specialized middleware to ensure that point-to-point communications can be completed and can be handled in a designated time frame.”

To hear more detail about this topic, including the capabilities of both ADLINK Technology and NVIDIA, check out the recent podcast featuring experts from the two companies.

Rich Nass is a regular contributor to Embedded Computing Design. He has appeared on more than 500 episodes of the popular Embedded Executive podcast series, and is a regular contributor to the Embedded Insiders podcast.

Rich has been in the engineering OEM industry for more than 35 years, and is a recognized expert in the areas of embedded computing, Edge AI, industrial computing, the IoT, and cyber-resiliency and safety and security issues. He writes and speaks regularly on these topics and more.

Rich is currently the Liaison to Industry for the Embedded World North America Exhibition and Conference, and has held similar positions with the global Embedded World Conference and Exhibition.

Previously, Rich was the Brand Director for UBM’s award-winning Design News property. Prior to that, he led the content team for UBM Canon’s Medical Devices Group, as well all custom properties and events.  In prior stints, he led the Content Team at EE Times, handling the Embedded and Custom groups and the TechOnline DesignLine network of design engineering web sites.

Nass holds a BSEE degree from the New Jersey Institute of Technology.

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