Autonomous robots have the potential to revolutionize industries such as construction, agriculture, and disaster relief by increasing efficiency and safety. However, one major hurdle remains: machines from different manufacturers cannot easily communicate with or collaborate with one another. This lack of interoperability leads to costly customizations and complex programming whenever new machines are integrated into existing autonomous processes. The IMARO project addresses this challenge by developing universal middleware that enables seamless, secure, and spontaneous networking of autonomous machines, regardless of their manufacturer. This innovation is expected to unlock new levels of collaboration, flexibility, and scalability for autonomous systems in demanding off-road environments.

The IMARO project is dedicated to developing a vendor-neutral middleware platform that acts as a translator and coordinator for autonomous machines. This middleware will enable robots of various types and from different manufacturers to form coordinated swarms and adapt dynamically to changing scenarios and requirements. The solution is designed to be open, scalable, and robust, ensuring that machines can be integrated into cooperative systems on an ad hoc basis without requiring extensive reprogramming. Field tests are being conducted in real-world scenarios such as construction sites, agricultural areas, and disaster zones to demonstrate the practical benefits of the middleware. Ultimately, the project aims to establish a standardizable key technology that supports sustainable automation and opens up new opportunities for innovation, particularly for small and medium-sized enterprises.

• Development of generic, modular middleware that enables ad hoc networking and coordination of heterogeneous autonomous robots.
• Ensuring interoperability between different manufacturers, platforms, and application areas without the need for individual interface adaptations.
• Creation of standardized models and metrics for describing and evaluating the autonomy capabilities of machines.
• Demonstrating the effectiveness of the middleware in real-world application scenarios such as construction, agriculture, and disaster relief.

• Specification: Analysis of existing software solutions and frameworks, definition of application scenarios, and specification of a modular system architecture with a focus on modularity, real-time capability, and extensibility.
• Development of Metrics: Definition of quantitative and qualitative metrics for the objective evaluation of the middleware’s performance, scalability, and reliability.
• Adaptation & Connectivity: Development of mechanisms for the dynamic integration and adaptation of new machines, including generic interfaces and adaptive integration strategies.
• Implementation: Building on established frameworks (such as FINROC and ROS 2) to ensure robust, service-oriented, and real-time-capable middleware.
• Swarm Demonstration: Implementation and testing of the middleware in real-world swarm scenarios by networking multiple autonomous vehicles from different manufacturers.
• Validation: Systematic measurement and analysis of system performance in practical applications, culminating in public demonstrations.