Blue graphic showing various forklift trucks and mobile robots standing in front of an industrial background.
Blue graphic showing various forklift trucks and mobile robots standing in front of an industrial background.
Mobile Robotics

Efficient fleet management: How to successfully orchestrate heterogeneous robot fleets

With the growing use of mobile robots in warehouses, it is becoming increasingly important to ensure smooth cooperation between manual and automated vehicles. But how can a mixed fleet be coordinated efficiently?


In the dynamic world of warehouse operations, automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) are often an integral part of intralogistics operations. By 2028, 50 % of large companies will use mobile robots in their warehouse or production operations1. 40 % of large companies will use heterogeneous vehicle fleets in their warehouse operations within the next five years1. While they relieve workers and take over tasks, they also increase the volume of traffic. This becomes particularly challenging if the traffic in the warehouse is not fully transparent and centrally managed.

Challenges of mixed warehouse operations

As not all tasks can be automated by mobile robots, the use of manned vehicles is still necessary. However, mixed operation raises various challenges:

  1. Accidents and repair costs: Collisions between manual and automated vehicles are not uncommon and can cause considerable damage and high repair costs.
  2. Downtime: Every accident leads to costly downtime as damaged vehicles need to be repaired. This leads to production delays and loss of revenue.
  3. Operational inefficiency: Manual and automated vehicles are often difficult to coordinate as they operate on different systems and platforms. This leads to longer waiting times and inefficient use of resources. Operations become inefficient when deadlocks and congestion affect productivity and AGVs/AMRs have to be moved manually, for example, which causes additional work, waiting time and frustration on the store floor and can affect the efficiency of the entire operation. The dissatisfaction and impatience of manual drivers can contribute to reducing the acceptance of mobile robots.
  4. Coordination difficulties: As an organization's robot fleet grows, simple point-to-point API integration will no longer suffice. Companies will need an advanced orchestration function (such as provided via the VDA 5050 standard) that is able to assign work to the right robots. This should be based on real-time information that takes into account the characteristics of the activity and the capabilities of the different automation agents. Effective coordination and operations management are crucial to ensure the smooth running of automated and manual vehicles and maximize productivity1.

Integration into a common fleet management system

The solution to these challenges lies in the integration of manual vehicles into a powerful fleet management system. By 2026, more than 50 % of companies using intralogistics robots will be using a multi-agent orchestration platform1. Here are some reasons why this can be an extremely worthwhile investment:

  1. Cost savings: Integrating manual vehicles and mobile robots into a common system can help reduce accidents and downtime, thereby avoiding costs.
  2. Increased efficiency: Interoperable fleets orchestrated by a common fleet management system enable optimal coordination and utilization of available resources. This leads to shorter waiting times and overall more efficient operations management.
  3. Safety improvement: Integration enables better monitoring and control of overall fleet operations, minimizing accidents and increasing safety for employees and equipment.
  4. Flexibility and scalability: The seamless integration of new manual vehicles into a fleet management system provides the flexibility and scalability needed to meet changing requirements.
  5. Sustainability: By extending the life of manual vehicles, the integration contributes to more sustainable operations and saves resources.



VDA 5050-capable fleet management systems

A crucial aspect of integrating manual vehicles into a fleet management system is the support of standards such as VDA 5050, which defines uniform interfaces and protocols for seamless communication and coordination between vehicles and higher-level systems. By implementing VDA 5050-compliant solutions, companies can improve the interoperability of their fleets and further increase the efficiency of warehouse traffic.

The integration of manual vehicles into an existing VDA 5050-compliant fleet management system is therefore a decisive step towards increasing efficiency in warehouse operations and reducing costs. To achieve this goal, it is necessary to retrofit manual vehicles with suitable technologies and ensure effective real-time localization and tracking. There are various technologies available to make this possible. The proven laser-based "Simultaneous Localization and Mapping" (laser SLAM) technology of autonomous vehicles is often also used in manual vehicles.

Laser-based localization technology forms the basis

Laser SLAM offers an advanced method for localizing manned forklift trucks and mobile robots in industrial environments. Compared to other technologies, it is highly precise with comparatively low commissioning costs. Vehicles are equipped or retrofitted with a laser scanner for this purpose. The sensors send laser beams and measure the reflections of objects in the environment. At the same time, the algorithm analyzes the vehicle's movements and creates a real-time map of its surroundings. This simultaneous mapping and localization function makes it possible to locate and navigate vehicles in real time, even in dynamic warehouse environments.

Precise real-time localization with the ROKIT Locator

With a laser-based localization software such as the Rexroth ROKIT Locator both mobile robots and manual vehicles can be localized using the SLAM algorithm. The ROKIT Locator enables the precise detection of vehicle position and movement in real time – without any further infrastructure adjustments. The API enables seamless integration into existing (interoperable) fleet management systems. This enables precise coordination of the interoperable vehicle fleet. Manual vehicles can be monitored in real time, routes optimized and collisions avoided.

In addition, the localization software makes it possible to analyze and optimize the performance of manual vehicles. By continuously collecting data, companies can make further operational improvements that additionally increase their efficiency.

Localization pin on a blue background points to a position on a map. Various industrial vehicles are located around the pin as icons.

AMR, AGV or forklift truck – use the ROKIT Locator flexibly!

Vehicle integration in the Rexroth ACTIVE Shuttle Management System

Dashboard of the Rexroth ACTIVE Shuttle Management System (AMS) on a tablet that someone is holding in their hand.

With the ACTIVE Shuttle Management System (AMS), Bosch Rexroth supports the VDA 5050 standard.

With the ACTIVE Shuttle Management System (AMS), Bosch Rexroth supports the VDA 5050 standard and offers a fleet management system that simplifies the coordination of warehouse traffic. The central system can be used to control orders for autonomous mobile robots and manage traffic in the warehouse.

By supporting the VDA 5050 standard in the AMS fleet manager, Bosch Rexroth offers the possibility to connect manual vehicles by retrofitting them with the ROKIT Locator in order to reduce the challenges of accidents, operational inefficiencies and coordination difficulties in warehouse traffic. The AMS offers an orchestration function for VDA 5050-enabled vehicles and thanks to the "deep boarding" of selected vehicle types, it provides functional added value compared to generic VDA 5050 fleet management systems.

1https://futureiot.tech/orchestrating-the-heterogeneous-robot-fleet/. Retrieved on 07/18/2024.

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Jörg Heckel, Head of Projects Robotics, Bosch Rexroth AG

Author: Jörg Heckel

Position: Head of Projects Robotics