The July 2022 issue of IEEE Spectrum is here!

Close bar

Why Kiva Is Worth $775 Million to Amazon

Kiva's robots can make a huge difference to warehouse efficiency; watch these videos and see how

2 min read
Why Kiva Is Worth $775 Million to Amazon

On Monday, we broke the news that Amazon.com has decided to acquire Kiva Systems for more than three quarters of a billion dollars in cash. This is a heck of a lot of money, even for a company like Amazon, but as soon as you see what Kiva's robots are capable of, it'll make perfect sense.

In July of 2008, our esteemed editor wrote a beefy feature about Kiva, which is worth reading in its entirety. But if you're just looking for a snapshot of what Kiva can do for Amazon, check out these two vids: the first one comes from the 2011 Wired Business Conference, where Kiva CEO Mick Mountz discusses how Kiva robots think.

The fact is, Amazon is run out of warehouses, and the more efficient they can be in those warehouses, the more money they can make. Kiva makes warehouse operations significantly faster, of course, but it's more than that: using the robots means that Amazon can pack more stuff into a given space, they don't have to waste lots of money on heating or air conditioning or lighting, they don't have to spend lots of time training people, and they don't have to worry nearly as much about theft. Robots don't need overtime, healthcare, or 401(k).

That's all great news for Amazon, but they're buying Kiva, not just hiring them. We can only assume that it's obvious to this gigantic warehouse company that  Kiva Systems are the future of warehousing in general, and they want a piece (or all the pieces) of the action. Here's what Kiva managed to do for Zappos, for example:

For those of us who have been watching the robotics industry for a while, it's exciting to see things like this happen to companies like Kiva. Robots are tools that can do more than just serve as arms in factories: by making them smart and clever, they have the potential to transform all sorts of industries, and that makes them immensely valuable. And the field is still wide open. Kiva is just the tip of the iceberg when it comes to robotics, and with a tip the size of $775 million, that should give you a clue as to how big this iceberg actually is.

[ Kiva Systems ]

The Conversation (0)

How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman
LightGreen

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

Keep Reading ↓Show less