Automated Learning of Communication Models for Robot Control Software
Alexander Kleiner, Gerald Steinbauer, Franz Wotawa · 2008
Control software of autonomous mobile robots comprises a number of software modules which show very rich behaviors and interact in a very complex manner. These facts among others have a strong influence on the robustness of robot control software in the field. In this paper we present an approach which is able to automatically derive a model of the structure and the behavior of the communication within a componentorientated control software. Such a model can be used for on-line model-based diagnosis in order to increase the robustness of the software by allowing the robot to autonomously cope with faults occurred during runtime. Due to the fact that the model is learned form recorded data and the use of the popular publisher-subscriber paradigm the approach can be applied to a wide range of complex and even partially unknown systems.