Artificial Intelligence: Seeing Robots and the Logistics of Tomorrow
Artificial Intelligence: Seeing Robots and the Logistics of Tomorrow
Kay Schiebur on the AI revolution in logistics

No other technology will be as disruptive over the next few years as Artificial Intelligence (AI). The Otto Group is a forerunner in this field of innovation. With the aid of robots, it is set to revolutionize logistics. A strategic partnership with Californian start-up Covariant will help it do that.

The future is more tangible than ever before, and artificial intelligence is playing a decisive role in making it happen. A few months ago, most people wouldn’t have been able to imagine AI generating texts, images, complex processes, and programs at an astonishingly high level. Visionary researchers are working to continually improve its quality and manageability, at breakneck speed. We can only guess the extent to which this will revolutionize the world of work in the coming years. However, it is clear that we are at the beginning of an unprecedented transformation, including in e-commerce.

When it comes to the huge potential of AI, the discussion has so far mostly centered on digital language skills. Generally speaking, the focus is on digital products. But could a technology like ChatGPT also be applied to physical objects in the material world? For example, through robotics? The answer is yes. Californian start-up Covariant, considered by insiders to be the world’s leading provider of AI Robotics, has been at the forefront of this development since 2017. The Emeryville-based company has developed the world’s first foundation model for robotics. Put simply: Robots will be enabled to make decisions autonomously. This in turn will enable the world of logistics, i.e. everything involved in the flow of goods, distribution, packing, and movement of goods, to be reconceived and reorganized. And all this will be done in tandem with the Otto Group, which is entering into a strategic partnership with the company.

2017

The company was founded in 2017 by Pieter Abbeel, Peter Chen, Rocky Duan, and Tianhao Zhang, who in Silicon Valley are considered the most innovative pioneers in the area of artificial intelligence and deep learning.

222 mio

Since its establishment, Covariant has raised USD 222 million of investment capital.

Order Picking Competition

In an order picking competition put on by robotics company ABB, Covariant’s robots were the only ones, out of 20 participating tech companies, that managed to complete all the tasks set for them.

Logistics Is the Beating Heart of E-Commerce
Logistics is like an engine that keeps the retail sector going, particularly online retail. Customers generally only see the final stage of logistics: delivery. But to make it possible, delivery must be preceded by a number of other steps, all of them crucial and very labor-intensive, i.e. picking (selection), sorting, and packing of individual goods for individual orders. Because fulfilment centers often contain tens of thousands of different products, this process is, on the one hand, very complex and, on the other, very painstaking and repetitive, and there is an increasing shortage of qualified personnel in this area. The Otto Group is therefore taking a visionary step. In these times of crisis, it is investing in the future: In the Otto Group’s fulfilment centers, more than a hundred AI robots will be deployed to handle the order-picking process. The start is planned in the centers in Haldensleben and Altenkunstadt.

Completely Rethinking Processes
Raphael Adrian Maier, Group Vice President Supply Chain Management, plays a key role in the cooperation with the technology start-up. He explains: “AI Robotics offers us the possibility of responding to several challenges in the area of logistics. The skills shortage can thus be compensated for. But first and foremost, they enable us to continue operating our fulfilment centers close to our customers. This strengthens Europe and even more so Germany as a location for doing business.”

The Otto Group discovered the Covariant’s visionary technology through targeted research. Initial meetings were promising, but the decisive step was a visit to California. Maier remembers: “We watched the robot arms sorting objects. This is a familiar activity for people: We can recognize things and know how to pick them up. A machine has to learn that. The way the robots handled an apple was very impressive. At first, the arm was unable to grip it. It, therefore, rolled the apple around a little to get a feel for it, after which it succeeded in lifting it. On its next attempt, it succeeded immediately. We could see that the AI was undergoing a learning process.” You can see exactly what this means in this video: The AI-trained robot determines autonomously how different objects can to gripped and moved.

Seeing Is the Crucial Factor
In the last three decades, great progress has been made in the automation of in-house transport. We are now at the beginning of a new chapter in which the focus will be on automating laborious and costly manual work. The challenge lies in the fact that we are dealing with a dynamic situation and a great deal of diversity in terms of the form, color, and quantity of the goods to be processed. Large-scale robot-supported picking and placing can only be successful if it is supported by artificial intelligence which equips the robots with “eyes” and a “brain” for interaction with a dynamic environment. The watchword is “General AI”—i.e. an artificial intelligence that not only makes decisions in preset pathways, but that can also handle unknown situations. This is where the Covariant Brain comes in, a universal AI platform with a six-camera vision system mounted above the robot arm that not only acts as its eyes but also teaches the robot to learn from past experiences . Furthermore, all Covariant robots learn together as a fleet, being connected to the same universal AI brain—this means that operative improvements are automatically distributed throughout the network. However, Covariant has long been thinking ahead.

Logistics is an ideal area for working with AI. It offers a typical dynamic scenario. The machine must be able to recognize objects and then decide what to do with them. For us, however, this is only the beginning—we will learn along with logistics. The aim in the long term is to be able to automate numerous types of processing in complex physical environments. The boundary between the digital and physical world then becomes fluid.

Peter Chen, Covariant co-founder of Covariant and AI visionary

Commitment to the Future
Group Service Director Kay Schiebur sees the cooperation with Covariant in a similar way: “The point is not just to make logistics a little more effective. It is still largely unforeseeable what further possibilities there will be for the use of general AI in or outside of logistics. However, it is clear that we are facing that future with courage and curiosity.”

Fears of a “dark warehouse” in which all the work is handled by robots are misplaced. “We tend to take the opposite attitude,” says Raphael Maier: “With the introduction of AI, more capacities will be freed up for complex, creative, and value-adding activities. Also, large numbers of experts are needed to control and inform the AI.” Kay Schiebur stresses that the cooperation with Covariant is a typical Otto Group investment, as it resonates with two core values of the company: performance and innovation. “When a difficult market environment prevails, it is important that investments in the future do not fall by the wayside,” Schiebur stresses. “We are investing here and now in our future viability, in order to strengthen our leading position in Europe.”


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