AI News, German Warehouse Robots Tackle Picking Tasks

German Warehouse Robots Tackle Picking Tasks

Companies like Clearpath, Fetch, and Locus Robotics are doing some amazing work in order fulfillment and other warehouse tasks by developing mobile platforms that can autonomously and intelligently ferry items between locations.

The hard part is getting those robots to pick items from shelves, and apparently it’s reallyhard: Amazon (whose warehouse robots are capable of tranporting items but not picking them) is holding its second Picking Challenge at RoboCup this year, and even with teams of researchers all collaborating on picking tasks with very expensive robots, results have been good but not inspiring.

This sounds restrictive, but you can imagine how much of (say) your average fulfillment warehouse consists of books and boxes of a size that Toru can handle, and you’re looking at a pretty significant percentage of robot-pickable stuff.

Depending on the frictional properties of the books and pamphlets, pulling one pair out might drag the pamphlet below along with it, and I’m wondering if the robot would even be able to tell, much less deal with the problem, whereas it would be effortless for a human.

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As it turned out, such a machine would be far too expensive for the consumer market, but the idea of a robot who could handle individual and single items, and not just a whole box or tray, was born.

After only a short time of working on TORU, we caught the attention of Siemen’s Novel Businesses investment arm and gained their backing which allows us to continue innovating and elevating our robots to the highest level.

The former requires workers to walk to shelving areas and manually pick goods, which has a high dependence on the staff hired, with high salary and processing costs.

With the interface between the warehouse management system and the robots now established, the orders - that were sent to a human workforce via PC or printed paper list - will be sent to the robot.

Then TORU will measure the dimensions and orientation of the item by analysing the image it sees through the its camera - with this information it will calculate the movements of its gripper before grasping the object and storing it in its internal shelves for transit.

Sensors and computer chips are becoming cheaper and providing better performance, new programming languages are being established and evolving, but most importantly, the actions of robots are no longer predetermined at the time of programming and building them.

they are reacting on behalf of what they sense from their environment, which is particularly interesting when it comes to warehouse robotics as it means that humans and robots are able to work together in a much more succinct and productive fashion.

TORU can operate in the warehouse where individual orders are picked manually - this also includes processes in factories where TORU can bring individual objects and components from storage direct to the production line.

While the first two focus on picking individual items from shelves using precision instruments designed to grip and carry box shaped items and other cuboid objects, TORU Flex uses a 6-axis arm with different end-effectors/grippers.

"Hi, I'm Toru, the intelligent warehouse robot"

The robot is capable of seeking out and gripping individual square objects from a shelf or storage container on a shelf.

Working with a batch size of one, meaning one single piece of warehoused merchandise per pick as is common in the B2C mail-order business, humans can achieve 120 picks per hour on average.

Toru currently manages 80 picks, but upgrades are slated to bring that number up to 120 by May. One issue limiting its performance is the maximum possible controllable speed of the gripper arm.

That speed cap is just one of the many safety mechanisms and behavioral rules integrated into Toru to ensure that it can work safely around humans and other machines — after all, there are a variety of regulations at both the legal and insurance level to be accounted for.

If a mail-order firm working solely with rectangular warehouse inventory — a B2C bookstore, or a shoe store — wanted to work with robots, then the picking process could be upgraded to 100 percent automated right now.

Magazino also intends to work with a flexible billing model: instead of buying each robot, the startup will provide the hardware to mail order retailers and logistics companies and charge by the pick.

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