America in Motion AGVs

Automation Advances Chart New Course for AGVs

Jan. 29, 2020
America in Motion founder explains how machine learning, vision and speech on a universal PC-based platform can move mobile robots forward for intralogistics.

Tommy Hessler, CEO of America in Motion (AIM), has worked with automatic guided vehicles (AGVs) since the mid-1980s. During that time, the AGV industry has repeatedly forecast exponential growth but has not widely embraced leading-edge technologies, says Hessler, who has assisted the National Institutes of Standards and Technology (NIST) with defining AGV standards. However, Charlotte, N.C.-based AIM has always taken a different route.

Since Hessler and Executive VP Theresa Blasius founded AIM in 2007, the company has worked on numerous custom AGV projects using Beckhoff Automation technologies. Doug Schuchart, Material Handling & Intralogistics Manager for Beckhoff Automation LLC, recently spoke with Hessler about the future of AGVs and the industry.

Schuchart: What trends and technologies are changing the course of the AGV industry?

Hessler: In the broader industrial world, many manufacturers and OEMs are embracing Industry 4.0 and IoT concepts. But in the world of automatic guided vehicles, this has not hit home yet—despite how smart and capable Industrial PCs (IPCs) have become. America in Motion is adopting these new concepts and upgrading AGV controllers and software platforms to implement Industrie 4.0 concepts. We are using PC-based control from Beckhoff to increase functionality, for example, by adding advanced speech, vision, cloud connectivity and machine learning capabilities. As a result, AGVs are becoming a PLC on wheels.

Schuchart: How are customers influencing these changes?

Hessler: Our customers want to collect actionable information from every aspect of their business. Because AGVs drive around the plant all day, they offer a valuable way to collect operations data as mobile IoT devices. However, the AGV control platforms widely available today do little more than navigation, and they rely on outdated communication via CANopen or another legacy fieldbus.

The system openness and multi-protocol communication capabilities available through the EtherCAT industrial Ethernet system help us incorporate CAN devices now, but we would like to use only EtherCAT in the future as we standardize on Beckhoff.

The capabilities of TwinCAT and other technologies allow us not only to collect information but also to present it using via HTML5-based TwinCAT HMI software and standard web servers.

Schuchart: What data types are most useful to distribution center and intralogistics managers?

Hessler: There are three main categories. The first is performance data, which means the measurement of how many loads are moved per hour per AGV. Beckhoff offers much greater capabilities to collect and graphically present this data.

The second category is safety. These autonomous vehicles move around busy facilities among people, using safety bumpers, light curtains and other safety devices, per ANSI and ISO standards. We want to collect information any time these safety devices are triggered and take a photo, automatically blurring faces to protect privacy, to determine what happened. There are black-box solutions for this that require the AGV to be manually plugged into a separate computer. We are developing solutions that will tie the functionality into our overall control infrastructure that will run on a CX2042 Embedded PC and transmit data wirelessly.

The third category covers system performance, which means keeping statistics on routes and efficiency changes by day or hour. This allows facilities to optimize AGV routes with incredible results.

For example, I performed a study for a dominant beverage producer on one warehouse: Without optimization, it required roughly 180 AGVs, but once optimized with better data collection and analysis, it only needed 32. So with this data, the increases in efficiency are substantial. Soon, this optimization will leverage neural networks, such as those made possible by TwinCAT Machine Learning. There again, Beckhoff helps us start at step seven.

Schuchart: Beyond functional safety, do you foresee TwinCAT Vision enhancing AGV systems?

Hessler: I see software for image processing, such as TwinCAT Vision, as enabling technologies for AGVs to find pallets and racking more efficiently using GigE cameras. Today AGVs use lasers or a guide taped onto the floor to determine their X-Y potions in warehouses, but they can’t identify specific objects or racks. This requires time-consuming measurement, and if anything changes, engineers have to return to measure again.

On top of that, if customers want to move the guide paths even slightly, they often don’t have the proper tools to do so. Some AGV vendors play games and do not provide customers the rights to a facility’s definition tables. This isn’t their proprietary information; it’s simply your floorplan.

By implementing 128-beam lasers that update 50 times per second with integrated vision and machine learning, the AGV could basically survey and map the distribution center without human involvement, adjusting if shelving positions or height changes. A pallet could be located anywhere, but once it is identified, the AGV calculates the path and simply picks it up on its own. With open, PC-based control technologies in a single platform, customers can better manage their data and operations.

Schuchart: Are warehouse workers and managers excited or apprehensive about these technologies?

Hessler: Many times selling AGVs seems like selling a car in the 1890s: The technology is already unfamiliar, and if you started to talk about things way ahead of their time, like CD players, no one would understand anything. Management wants to improve throughput, but doesn’t know why they need an AGV, how it works or if it’s safe, even though it has light curtains all around. We make an effort to guide everyone through the experience and give AGVs more familiar, human attributes. We make the vehicles unique colors and give them names, like Frank and Dottie.

Now, using TwinCAT Speech, we are designing a better system, especially for picking operations. Instead of typing “I’m done” or pushing a button after every pick, operators with a headset will simply talk to the AGV by name and have both hands available to pick boxes at the next stop.

Having a mobile robot by your side that listens and verbally responds to you will enhance operations and make U.S. businesses more competitive for workers and management, and that’s what we want. People often feel automation takes away jobs, but we named our company America in Motion because we want to do the exact opposite. Our vision is to make robots friendly so they really collaborate and add value rather than compete against humans. Implemented correctly, we can keep the whole production and desirable jobs here in America. With the TwinCAT software platform and IPC hardware from Beckhoff, we can continue innovating to keep manufacturers and distribution centers moving forward at full speed.

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