System interdependence analysis for autonomous robots

With the increasing complexity of robotic systems, system robustness and efficiency are harder to achieve, since they are determined by the interplay of all of a system's components. In order to improve the robustness of such systems, it is essential to identify the system components that are crucial for each task and the extent to which they are affected by other components and the environment. Such knowledge will help developers to improve their systems, and can also be directly utilized by the systems themselves, for example, to detect failures and thereby correctly adjust the system's behavior. In this article a method of system interdependence analysis is presented. The basic idea is to learn and quantitatively evaluate the coherence between performance indicators of different system components, as well as the influence of environmental parameters on the system. To validate the proposed approach, system interdependence analysis is applied to the navigation system of an autonomous mobile robot. Its navigational methods are presented and suitable indicators are derived. The results of using the method, based on experimental data from an extended field experiment, are given.