One of every five beauty purchases online is made via the Amazon marketplace, according to a new report.
The merchant and technology company has introduced the RBO Hand 2, which can grasp most of the merchant’s 48,000 grocery products to fill online orders.
U.K.-based web grocer Ocado wants robots to take charge. At least, that is, when it comes to warehouse picking.
Merchant and technology company Ocado Group Plc has unveiled a robotic arm for warehouses that can grasp many of the merchant’s 48,000 items.
To avoid damaging sensitive and unpredictably shaped grocery items, the new robotic arm, called the RBO Hand 2, uses an orchestrated interaction between the hand, the object being grasped and the environment where the arm is working, according to Ocado.
"We are pursuing a new direction for robotic grasping by developing robot hands that can safely pick easily damageable items such as fruits and vegetables,” says Graham Deacon, robotics research team leader at Ocado Technology. “[The hand] offers a versatile, cost-effective and safe solution for robotic grasping and manipulation that integrates very well with Ocado's highly automated warehouse retail solutions."
The Ocado Technology unit of Ocado develops robotics, machine learning, simulation, data science, and forecasting and routing systems for its online grocery operation. The technology unit also markets its e-commerce platforms and technology services to other online retailers, including U.K.-based supermarket Morrisons, which sells online and in stores. Ocado says Morrisons is the fourth largest grocer in the United Kingdom.
Ocado, No. 23 in the Internet Retailer 2016 Europe 500, says its Ocado Technology unit and the Technische Universität Berlin (TUB) developed the arm, which is part of the SoMa project—a European Union-funded, Horizon 2020 program for research and innovation in humanoid robotics. Horizon 2020 is one of the largest EU research and innovation programs, backed by nearly €80 billion ($86.39 billion) in funding over seven years—2014 to 2020—in addition to private investments.
The SoMa project also includes researchers, academics and scientists from the University of Pisa, the Italian Institute of Technology, Deutsches Zentrum fur Luft- und Raumfahrt (DLR, the German aerospace agency), the Institute of Science and Technology Austria, and Disney Research Zurich.
Ocado, which posted a 14.7% increase in 2015 web sales to $1.4 billion pounds ($1.74 billion) and has more than 500,000 active customers, has long focused on developing technology to boost sales. In December, Ocado opened a highly automated warehouse in Andover, Hampshire, U.K., which includes hundreds of robots swarming on a grid the size of several soccer fields. Ocado Technology is also involved in the SecondHands project, another Horizon 2020-funded program that aims to design a collaborative robot that can learn from and offer assistance to warehouse maintenance technicians.
Ocado also has employed for more than eight years a team of data scientists that has worked on several projects, including the development of a system called Instant Order that will predict a returning shopper’s order based on her purchase history. It also has used data science to improve warehouse operations in other ways beyond developing robots, says Dan Nelson, head of data for Ocado.
For example, the retailer regularly rearranges the location of items in its warehouses based on orders it received that are slated to be picked, packed and shipped the next day in an effort to get orders out the door more quickly, Nelson says.
Ocado also is implementing a system, built in-house, to eliminate manual review and sorting of the more than 2,000 daily customer service emails it receives. About nine months ago, Ocado began working on this new way to manage emails more efficiently using machine learning and Google’s TensorFlow, an open-source software library for building machine learning frameworks. Machine learning is a process by which computers can learn over time when they are exposed to new data, essentially modifying the computer’s initial programming.
The new system takes emails as they come into the contact center and determines if they contain positive or negative feedback. Next, it assigns a strength to the positive or negative sentiment of the email. Finally, it tags the message with a description of its content, such as a request for website help, a complaint about delivery, a product-related issue or a cancel order request. Based on all of that data, each email is immediately prioritized on how quickly it should be read and answered, Ocado says.