Robotics

An exampleof increased packaging automation muscle in the fulfillment center and e-commerce space came from ABB, which debuted its new Robotic Item Picker (1) at the show. The Item Picker helps customers automate order picking and sorter induction operations, and it fulfills ABB’s vision of a fully automated warehouse by combining automated storage with automated order picking, the company says.

“This is a fantastic new application that we’re unveiling here at PACK EXPO,” says Ali Raja, global marketing and sales director for ABB. “It’s powered by ABB’s own AI software, some of the latest techniques in machine vision and, of course, our famous robot planning. All of that in combination allows us to be the fastest item picker on the market. We’re achieving peak throughput of 1,500 picks per hour.”

Target customers include system integrators serving e-commerce, logistics, healthcare, and CPG. It also takes aim at end-user customers in 3PL, e-commerce, and fulfillment centers, all to serve common applications such as order picking, replenishment, receipt picking, and fashion sorting.

Raja says the Robotic Item Picker provides high picking quality of 99%+, meaning no double picks and no dropped items. He says it also o ers ease of use and it’s easy to integrate. Plus, it has easy-to-operate application control configuration and parametrization for integrators and sophisticated, yet intuitive controls for end users. He also claims best-in-class price/performance ratio. a related video at pfwgo.to/7831 .

Autonomous product picking

The result of a decade of R&D, the Bastian Solutions SmartPick fuses a warehouse execution system with a six-axis robot, machine vision, and advanced artificial intelligence (AI) to create an autonomous product picking system (2).

This advancement in robotic order fulfillment o ers customers faster, more accurate orders while answering the need for a more reliable solution that can grow alongside operations—turning a goodsto-person (GTP) system into an e cient goods-torobot (GTR) system.

Bastian Solutions presented its first vision-driven bin-picking robot back in 2010. It relied on a pretrained vision platform, transporting products from one stationary bin to another. The company has improved on those capabilities considerably since then, and can now pick a complex assortment of products from the back end of a GTP system with 99% accuracy.

“The key to the SmartPick is the autonomy—the ability to route orders through our warehouse execution system down to the robot autonomously with pickable products for the robot to handle,” says Steven Hogg, applications engineering manager for Bastian Solutions. “We also have an AI-based vision system that has deep machine learning to where we can learn on the fly—we don’t have to pre-program any of the images in, and the vision system continuously improves as it picks.” At the heart of the system is a robotic piece-picking sys- tem with custom-designed end-of-arm tools that can adapt to a wide variety of product shapes, sizes, and surfaces, he adds.

The system integrates seamlessly with Bastian’s ML2 autonomous mobile robot (AMR). “It is designed to be autonomously routed throughout the warehouse facility or throughout the manufacturing facility to deliver products to various manufacturing lines or also order fulfillment,” Hogg says. “It can have a static stand on top of the AMR or a conveyor to route totes between the various production lines.”

The AI and physical systems integrate with Exacta, the company’s proprietary intralogistics software, to enable the cells to run with higher autonomy. “This is what is driving the orders being brought down to the autoserve port,” Hogg says. “This right here is showing the bin that’s being delivered to the workstation. The robot is working in the background to start and stop the cell. We go to the individual bin and are picking pieces out and are placing to the AMR ML2.” a video of the system in action at pfwgo.to/7832

SmartPick is a turnkey GTR fulfillment system that increases picking throughput, adjusts to labor availability, reduces picking errors, allows for 24/7 automated operations, and improves customer satisfaction.

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In a trend toward food processors designating less space for their palletizing operations, EnSight Solutions has developed a fenceless robotic palletizer (3) that gets the job done in a footprint of just 12 x 5 ft. The system combines Sick safety sensors with a Stäubli collaborative robot (cobot) to eliminate the need for fencing.

“With our area scanners, as the robot moves, you have a warning area where the light will turn yellow. It’ll move the robot very slowly,” explains Heath Clifton, director of automation and controls for EnSight Solutions. “As you walk in closer, you’ll get a red area, which is a safety stop for the robot.

As you move back out of the area, it’ll slowly start speeding up. And then once you get into the green area, it’ll move back to its full speed.”

Unlike standard robots, the payloads that cobots can handle tend to be smaller. The Staübli cobot, however, enables larger payloads. “The thing that di erentiates our cobot palletizer from others is it can lift up to 75 lb,” Clifton says. “If we’re doing a single pick, we can pick up to 18 boxes a minute. But with a 75-lb weight limit, we can pick up multiple boxes at a time to hit a higher rate.”

Stäubli also has cobot options with hygiene standards suitable for food processing areas. “One of the great options about our palletizer is that it’s a full stainless-steel design,” Clifton says. “We’re using a Stäubli robot, so it’s a full washdown robot as well. It’s a great application for the food industry. You can put it in a full washdown room if you’re palletizing in there, or a secondary pack application that’s wipe-down.” a video of the system in action at pfwgo.to/7833 .

Democratizing AI

Artificial intelligence (AI) applications have been growing rapidly in a variety of industrial technologies, ranging from data analytics and quality inspections to autonomous mobile robots. Now the technology is being applied to robotic grasping applications to enable accurate picking and placing of random objects in unstructured and changing environments.

Siemens says it is working to democratize AI-enabled robotics by encapsulating systems for complex problems in easy-to-use software. To this end, the company is developing an as-yet-to-benamed software technology designed for use by system integrators and OEMs to create cost-effective, advanced AI-driven piece-picking systems that can “reliably pick and place objects that are unknown to the system at runtime.”

Traditional automated pick-and-place systems follow fixed, pre-programmed routines in a structured environment. Applying AI enables robotics to perform generic tasks in unstructured and dynamically changing environments.

Explaining how the technology Siemens is developing di ers from the use of 3D vision to enable robots to pick and place random objects, Eugen Solowjow, head of the Robotics & AI Research Group at Siemens, says, “Picking and placing unknown objects is still relatively new. It has existed for, at most, two years in the market and, up until now, has not been very commonly distributed. These existing systems rely on AI—more precisely,