Middleware for Efficient Programming of Autonomous Mobile Robots

Programming of autonomous mobile robots is subject to a set of unique requirements, which differ significantly from pure software projects and programming of stationary robots. Despite severe constraint on the payload and thereby limited available computational power, real-time constraints for physical interaction of the robot with its environment must be satisfied. Furthermore, the complexity of robots, the uncertainties in sensors and the interaction with the environment and the cooperation of multiple robots leads to especially difficult conditions regarding testing, debugging, monitoring and analysis. The present thesis discusses the specific requirements on runtime efficiency of middleware. The developed methodology reduces the overhead for local information exchange in a message-oriented middleware and is transparent for the involved endpoints. Additionally, the publish/subscribe messaging system is extended with filtering functionality, which is performed directly at the publisher-side in order to considerably reduce the utilized resources. Based on this further methods have been developed to distributed record data and replay them synchronized, which enable an efficient offline-analysis of intrinsic data of multiple robots as well as external reference data. The offline-analysis of voluminous data pools, which is commonly a very time-consuming and error-prone procedure, is significantly accelerated with automated analysis capabilities which enable an objective evaluation and analysis of autonomously operating teams of cooperating robots. The presented concepts have been implemented both in the robotics middleware RoboFrame and on-top of the open source project Robot Operating System (ROS). The developed software serves as the foundation for a set of real-world applications with wheeled, four-legged and humanoid robots