The CEO and Chief Innovation Officer of Vecna Robotics, Dan Patt and Daniel Theobold, came in to see us at the ARC Advisory Group. We were already very bullish on the autonomous mobile robot (AMR) industry’s potential to improve warehousing and order fulfillment, but Vecna has some differentiators that make them a very interesting supplier.

While Vecna has been around since 1998, Vecna’s warehouse robots have only been generally available since last April. As the technology and market matured, Vecna decided to spin out a robotics business to focus on the promising logistics solutions marketplace.  They have invested tens of millions in R&D into robotics, have over a hundred issued and pending patents. Their early implementations have convinced large companies to expedite scaling of Vecna’s robots to enterprise operations.

The most noticeable thing about Vecna is that they offer a spectrum of robots designed for different tasks – each picking, case put or pick, pallet moves, and tuggers for the warehouse yard. In other markets, over time the market starts to move to providers that offer a broader selection of products and just “one throat to choke” if something goes wrong.

Vecna’s second differentiator is that their robots are highly collaborative. Amazon’s Kiva robots, for example, are designed to be operated in a section of the warehouse off limits to humans.  Vecna’s robots have vision systems that allow them to navigate safely around humans and share common transit paths. Their robots can also collaborate with other robots.  For example, a case pick robot might place a case on an AGV style robot that would then transport the case to a pallet build station.

Vision systems are driven by machine learning technologies.  At Vecna their robots come with “remote assist” capabilities. When it comes to training a vision system how to recognize and react to its environment, robots in warehouses are apt to discover things they have never seen, and don’t know how to react to.  In this instance, the robot can ask for help and a human can remotely provide supervision. This feature, they argue, also allows the robot to learn from its environment more quickly.

Mr. Theobald made the point that to solve a material handling problem, it is not always clear which robot or combination of robots and humans are best suited to solve the problem.  They offer simulation services – both discrete event simulation a physics simulation engine that makes sure the robot mechanisms are fully reacting to the laws of physics – to discover the solution with the best ROI. Historical data from a customer site can be fed into the simulation to improve the fidelity of the results.

The final differentiator that I found to be interesting, is that they are “platform agnostic.”  In other words, they can put their robot brain into a fork lift or tugger offered by another vendor and turn it into a robot.

ARC will explore the topic of robots in the warehouse in more detail next week at our 22^nd Annual Industry Forum in Orlando.  The warehouse robot panel is on Wednesday afternoon.