Distributed Software Architecture for AGVs for Separation of Dynamic and Static Obstacles

Abstract

The current trend towards mass customization confronts established mass production systems with specific challenges. In future production layouts will have to provide a high degree of flexibility and changeability in order to be able to respond to the demand for individualized mass products. This leads to a production network in which the work schedule of each product and thus the sequence of the individual production resources are flexibly arranged. A challenge in this scenario is the implementation of material transport between the machines. The use of mobile transport robots to realize a flexible connection of all material sources and sinks proves to be effective. However, the current design forms, as a monolithic AGV system or the use of flexible autonomous units, show specific weaknesses. The paper describes the research approach to establish an intralogistics service-based software architecture as an intralogistics execution system, which contains the elementary functions of a cross-platform use of mobile autonomous systems. One key application is to digitize the workspace of the mobile systems with a distributed system of infrastructural sensors. An embedded unit separates the scenario into static and dynamic obstacles. The method discussed also includes the aggregation of the images with static obstacles to a world model as a basis for global cross-platform routing. Thus, it is possible to include the static obstacles in an early phase of path planning. The researched architecture integrates a routing service, which offers a cross-platform map for each type of transport robots in use. The dynamic obstacles of the respective scenery are tracked directly by the embedded decentralized ceiling sensors. By combining the Hungarian method with a Kalman filter, the trajectory of the detected dynamic obstacles can be determined. Within the discussed method, this information is transmitted directly from the sensor units to the autonomous systems and allows the local path planner to avoid collisions. Within the implementation of both methods in an industrial demonstrator, the functionality of both services could be validated. The necessary real-time capability for a valid collision avoidance was not achieved due to the computing capacities in use.