A company called Kiva Systems is speeding up Internet orders with robotic systems that are modeled on random-access computer memory.
Squat orange robots and a set of adaptive algorithms are making it possible to deliver online orders faster. The system, so far installed in two giant Staples warehouses, allows workers to fill two to three times as many orders as they could with conventional methods. The startup that developed the robots and software, Kiva Systems, based in Woburn, MA, announced yesterday that it is rolling out a third system, for the pharmacy giant Walgreens.
Kiva Systems’ CEO and founder, Mick Mountz, likens the system to random-access memory chips. The warehouse is arranged in a memory-chip-like grid composed of rows and columns of freestanding shelves. The grid gives robots access to any product in the warehouse at any time. The robots serve two basic functions. First, they deliver empty warehouse shelving units to workers who stock them. The workers might stock one unit with a mix of paper, various types of pens, and computer software, all compiled from large pallets that had been delivered to the warehouse. Then, when a consumer submits an order, robots deliver the relevant shelving units to workers who pack the requested items in a box and ship them off. “We turn the whole building into a random-access, dynamic storage and retrieval system,” Mountz says.
If a consumer orders an item at 2 P.M. on a Thursday, he says, at 2:01, a robot can be delivering that order to a worker to pack. If an order has multiple items, robots will line up for workers as fast as the workers can pack the items. Once the items are packed, robots can pick up the boxes, storing them temporarily or delivering them to the appropriate delivery truck.
Mountz says that the system allows workers to fill orders much faster than conventional systems do because the robots can work in parallel, allowing dozens of workers to fill dozens of orders simultaneously. In one type of conventional system, workers have to walk from shelf to shelf to fill orders, and all that walking takes time. With the Kiva system, several robots can be dispatched to collect all the items in an order at once. The robotic system is also more efficient than conveyor-based systems, in which elaborate conveyors and chutes send boxes past workers who pack them as they go by. In such a system, the slowest part of the line, which could be the slowest worker, limits the overall speed. With the help of the robots, each worker fills an entire order, so one worker doesn’t slow everyone else down.
The robotic system is also faster because the entire warehouse can adapt, in real time, to changes in demand. Robots move shelves with popular items closer to the workers, where the shelves can be quickly retrieved. Items that aren’t selling are gradually moved farther away. More-conventional warehouses can also be adaptive, Mountz says, but it takes much longer to rearrange items.
A schematic of a warehouse floor. Shelves with fast-selling items are indicated in red. Blue squares show slow-selling items. Robots rearrange the shelves to keep the fast-selling items at the perimeter, close to packing stations.
Credit: Kiva Systems
Kiva’s system can adapt in other ways as well. If someone orders red pens that happen to be stored on the top shelf of a shelving unit, the system software directs that unit to a tall worker who can easily reach the pens. If red pens become hot sellers, the system will instruct stockers to stop putting them on the top shelf and start putting them on the middle shelf, where everyone can reach them. Also, the “peanut-butter and jelly algorithm,” as Mountz calls it, tells stockers to place items that are frequently bought at the same time on the same shelf. This can be changed as demand shifts from day to day, or between the summer and Christmas. Around Christmastime, the system can also direct robots to stations with the appropriate style of wrapping paper.
For Walgreens, the software will need to keep track of another parameter: expiration dates. It will ensure that items that can go bad, such as certain cosmetics, are sent out in the order that they’re stocked. (Walgreens will use the system to supply its store, not to fill orders from consumers.)
Kiva’s adaptive software is the key to the system. The hardware isn’t remarkable. The robots are small, wheeled boxes short enough to slip under a shelving unit and lift it up. The navigation system is simple, involving stickers on the floor, optical sensors, and Wi-Fi connections. The software prevents the robots from running into each other, and it keeps track of products on the ever-changing warehouse floor. Infrared sensors warn the robots of unexpected objects in their path–such as a box or a broken robot. Algorithms then kick in to reroute robots around the obstacle. The shelves themselves have lights that tell workers where to stock items, or where to find them in order to pack them. Bar-code scanners register when workers have packed an item and signal the next robot to move into position.
Kiva engineers are working on ways to improve the system. Right now, if a robot breaks down and maintenance workers need to go out on the floor to retrieve it, they virtually “rope off” the area in the warehouse, telling the software to route robots around the area. Mountz says that the engineers are developing a wireless device they call the Moses badge that will allow workers to walk safely among the shelves. The badge will signal the mass of robots to part and allow the workers through.
Rodney Brooks, professor of robotics at MIT, says that the Kiva system is a “very interesting” application of robotics. “It is increasing the productivity of people by having robots do the easy tasks and letting people do the hard tasks,” he says. “At the moment, it is incredibly hard for robots to manipulate varying objects. So Kiva leaves that to people and lets the robots do the relatively easy task of moving something from one place to another.” Eventually, Brooks says, robots may be able to handle all the tasks involved: “Don’t expect the current hard tasks for robots to stay hard forever.”
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