Automated transport systems have long been a central component of modern intralogistics. Traditionally, mobile transport robots (MTRs) are controlled via a central fleet management system that assigns routes, allocates tasks, and coordinates overall material flow. However, this approach comes with challenges: high costs, limited flexibility, and the risk of system failures. An alternative solution gaining traction is decentralized control via agent-based systems – a concept reminiscent of the way natural swarms function.
The Limitations of Centralized Systems
A traditional automated guided vehicle (AGV) system is organized through a central fleet management system. This system oversees the entire process, determines when and where each robot should operate, and ensures seamless interaction among all vehicles. Even simple actions such as turning, stopping, or signaling are dictated by the central control. Acting as a central hub, it collects and processes all relevant data.
However, this centralized approach has its drawbacks. If the connection to the control system fails due to maintenance, network issues, or system errors, the entire fleet comes to a halt. Even a single malfunctioning vehicle can disrupt material flow. Moreover, the IT infrastructure requirements are substantial: Beyond expensive hardware and software investments, companies must also hire staff and acquire support contracts to ensure smooth operations. For small and medium-sized enterprises, these costs are often prohibitive.
Decentralized Control: More Flexibility with Swarm Intelligence
An alternative approach is decentralized, agent-based control. Here, robots do not function merely as executors of a central command but rather as independent agents within an intelligent network. The vehicles communicate directly with each other, continuously exchanging information about position, speed, and routes, and making autonomous decisions.
"Transport robots are comparable to organisms living in a society," explains Michael Reicheicher, CEO of SAFELOG GmbH. "They all know the rules and regulations they must follow, but they can act independently."
This swarm intelligence enables dynamic and adaptive route planning. Traffic flow, intersections, and pathways are coordinated in real-time between the involved vehicles without requiring central oversight. Even peripheral devices like elevators or conveyors can be integrated into the system: An elevator, for example, can communicate its current floor location, allowing the robot to independently decide whether to use it and when.
Advantages of Swarm Control
Agent-based control offers several advantages over traditional fleet management:
High fault tolerance: Even if communication between individual robots is disrupted, the overall system remains functional. If a single robot fails, the rest continue operating.
Flexibility in process changes: Workflow modifications can be implemented incrementally without halting or reconfiguring the entire system.
Reduced costs: Expensive IT infrastructure, licensing fees, and maintenance contracts become unnecessary, making MTRs economically viable even for smaller businesses.
Independence from external systems: Unlike centralized control, which often relies on stable Wi-Fi connections, agent-based systems can operate without continuous data synchronization.
Applications and Hybrid Integration with Centralized Systems
While decentralized control offers many benefits, there are scenarios where a central fleet management system remains advantageous. This is particularly true for heterogeneous vehicle fleets where different manufacturers and systems operate together. The VDA-5050 interface standard ensures interoperability, allowing different vehicle types to be managed within a single fleet.
However, centralized and decentralized approaches are not mutually exclusive. A hybrid model can leverage the strengths of both: While the fleet management system provides overarching directives, individual robots retain the ability to make independent decisions. This approach enhances efficiency and robustness in intralogistics processes.
Conclusion: Autonomy as the Key to Efficiency
The shift towards intelligent, self-organizing robotic swarms represents a paradigm shift in intralogistics. Agent-based systems provide a cost-effective, flexible, and resilient alternative to traditional fleet management, ensuring smooth operation without centralized oversight. Companies adopting this technology benefit from greater adaptability, reduced failure risks, and long-term cost savings. The future of transport robotics lies in intelligent autonomy – a system that, like a living organism, can adapt dynamically to the ever-changing demands of logistics.