Revolutionizing Logistics: Otto Group’s Coordinated Autonomy Layer

At Nvidia’s GTC event, the retail breakout session ‘Leverage Physical AI to Simulate and Orchestrate Robotic Fleets for Retail Fulfillment Centers’ caught the attention of many. The session, featuring Germany-based Otto Group, showcased how the retailer is embracing physical artificial intelligence and moving it into real-world operations.

The complexity of a global supply chain is a significant challenge for Otto Group, which serves nearly 45 million customers worldwide and generates around €15 billion in revenue. To address this, the company has been working on incrementally optimizing processes and warehouses, but now it’s time for ‘big shifts.’

The Complexity of a Global Supply Chain

Running the supply chain end-to-end gives Otto control over what customers see, but it also entails greater complexity behind the scenes. This is why much of the work is happening in supply chain and logistics, especially around AI.

According to Martin Umland, vice president of supply chain management at Otto Group, ‘This is a very crucial moment. A lot of things had to be done in the last few years, working on incrementally optimizing processes and warehouses. Right now, it seems to be a moment where we can make very big shifts.’

From Optimization to ‘Big Shifts’

Umland shared more details about what that shift looks like during his session. He said Otto Group’s warehouses already run a mix of robotic systems, including autonomous mobile robots (AMRs) that move goods, shuttle systems, and robotic arms that handle specific tasks.

These systems were added over time from different vendors and for different use cases. They serve their purpose, but they don’t really work together. Instead of replacing them, Otto Group created what it calls a coordinated autonomy layer (CAL), which brings together different robotic systems so they can operate as part of a single workflow.

Mapping the Digital Twin

The project started with mapping a pilot warehouse. Otto Group used Boston Dynamics’ Spot robot dog to move through the aisles and scan the space, collecting data on the entire environment. After about a week, there was enough data to create a 3D digital twin of the warehouse in Nvidia’s Omniverse computing platform.

The digital twin turned out to be more precise than Otto Group’s own documentation. It also changed how the company worked with the space. Instead of treating the warehouse as fixed, Otto Group could test different setups and adjust how things move through the environment before making changes on the floor.

Testing Reality in Simulation

From there, Otto Group moved into simulation. It ran comparisons between different layouts and tracked how robots moved through each scenario. One area of focus was how often robots had to stop and restart their tasks. In one case, a revised layout reduced those stop-and-go events by about 20 percent, according to Stefan Borsutzky, co-CEO of Otto Group one.O GmbH, the company’s technology and consulting subsidiary.

‘The material flow was optimized, and the productivity of the robots increased. So, we used this result and implemented the new handover area already in the warehouse,’ said Borsutzky. ‘We are working towards a self-controlled warehouse under human supervision.’

The Coordinated Autonomy Layer

The complexity is less about any single robot and more about how they interact. If multiple machines move in the same space in a warehouse, typically, one doesn’t adjust to what the other is doing. Bringing the robots into a shared environment is the goal.

That’s where CAL comes in. This layer sits between the warehouse management system (WMS) and the machines themselves. As Borsutzky explained, CAL ‘takes the request coming from the WMS’ and assigns tasks across robot fleets. It also manages movement across the floor by routing robots and reducing the chances of incidents or collisions.

Conclusion

The Otto Group’s transition from manual labor to a Coordinated Autonomy Layer (CAL) represents a transitional moment in the evolution of logistics. By moving beyond individual ‘islands of automation’ — where robots from different vendors operate in silos — the company is creating a unified digital nervous system for its warehouses.

This case study highlights three critical shifts in the industry:

• The Power of the digital twin: Using tools like Nvidia’s Omniverse to create models more precise than original blueprints proves that ‘guessing’ on the warehouse floor is a thing of the past. Simulation enables risk-free experimentation, as evidenced by the 20% reduction in robotic stop-and-go events.
• A new role for human talent: As robots take over repetitive tasks, the human workforce isn’t being eliminated; it’s being elevated. The shift toward ‘oversight’ roles suggests a future where warehouse staff become orchestrators of technology rather than manual movers of goods.
• Infrastructure as software: By treating the physical warehouse as a flexible environment that can be ‘reprogrammed’ via simulation, Otto Group is proving that the most valuable asset in modern logistics isn’t just the hardware—it’s the data and the coordination layer that makes the hardware work together.