The overall structure and content of the MHI Promat and Modex events evolves very slowly from year to year. However, a prevalent theme seems to arise each year that differentiates one event from years prior. I’m told that robotic piece picking was the stand-out theme at LogiMAT last month and that theme will surely cross the pond to ProMat next month. I plan to spend a large portion of my time in Chicago at the piece picking exhibits. Here is my “must see” list for next month’s event.
My Robotic Piece Picking “Must See” List
RightHand Robotics (RHR) is the flagship piece picking provider (IMHO). I have visited the RHR booth at the last two shows and it is at the top of my list again this year, as I expect to see additional progress in the solution. The most commonly displayed workflows (applications) for RightPick have been goods-to-(robotic) picker, sorter induction, and automated packaging.
This team at RHR has been perfecting the problem of robotic picking in an unstructured environment for a number of years. And experience (time and number of attempts) certainly matters. Machine learning and algorithm optimization are essential elements to robotic picking productivity. At Modex, Leif Jentoff informed me that the solution’s software intelligence, driven by machine learning, is enabling the robots to pick 50 percent faster than they did a year prior. This productivity improvement is driven by a higher pick completion ratio and a shorter pick attempt time. RHR likes to use the three Rs – range of objects, reliability and rate – to frame the robotic piece picking problem. And I find it to be a useful framework for evaluating these technologies, as an increase in range surely complicates rate and reliability.
Vanderlande invested in the robotics development company Smart Robotics in 2017. Last month, Vanderlande announced a strategic partnership with Fizyr to develop artificial intelligence (AI) technology for its automated order picking solutions. The AI will be applied to Vanderlande’s piece-picking solution, Smart Item Robotics, to allow it to handle the large variation that is inherent in a piece picking environment. Smart Item Robotics is being applied in bin-to-bin and bin-to-belt picking. I hope this solution is exhibited by Vanderlande at ProMat next month.
Swisslog announced that it will exhibit its new generation ItemPiQ solution at the ProMat show. The robotic piece picking solution incorporates the KUKA KR AGILUS-2, a smart vision system, and a multifunction gripper. ItemPiQ is being promoted as an easily integrated complement to AutoStore. The Swisslog website states that ItemPiq can pick at a rate of up to 1,000 items per hour. I will be sure to visit the Swisslog booth to get a feel for the solution’s range and reliability.
Dematic also announced that it will exhibit its Robotic Piece Picking module at ProMat. Dematic will be offering two physical demonstrations of robotic piece picking, one of which will incorporate an advanced 3D vision solution utilizing machine learning methods. Dematic announced the launch of its robotics center of excellence about a year ago. I’m assuming the center of excellence contributed to the development of the Robotic Piece Picking capabilities to be exhibited at ProMat. I expect that the capabilities delivered by the advanced 3D vision solution allow the Robotic Piece Picking module to expand upon the range of potential items that can be properly handled.
TGW Systems showcased its Rovolution piece picking robot at Modex last year and will hopefully do the same at ProMat. TGW is promoting Rovolution as capable of picking at rates of 500 order lines per workstation per hour, and as an add-on to its FlashPick piece picking system.
The promotional materials for these piece picking robots often provide picking rates, weight ranges, and the methodology behind the capabilities. However, there is a clear trade-off between rates, range of items, and reliability. I believe each solution’s performance across these capabilities will provide insight into solution maturity, range of use cases, and the operational and financial feasibility of commercial application.