Detecting and locating faults in the control software of autonomous mobile robots

Control software of autonomous mobile robots is characterized by its fairly high complexity which is in conflict with stability. Complexity is caused by the software components implementing the basic functionality like planning, sensor fusion, actuator interfaces, and their interactions. Because of the high complexity but also the instability of hardware components and connections, and the underlying operating system, complete stability is very unlikely. But if we want to build a robot that is truly autonomous it has to deal with failures during its runtime without degrading the desired behavior or even worse failing to fulfill its mission. Hence, a diagnosis system on top of the control system which does monitoring the current behavior, locating the cause of a detected failure, and taking the appropriate actions is a necessity. To achieve this we introduce a model-based solution. This includes a model of software components and their relationships that are specified in the software architecture of the robot’s control system. This model is then used to derive root causes of a detected failure. The failure detection is based on observations. For this we use the concept of observers. If the monitored value exceeds its pre-specified boundaries, the observer raises a conflict which causes the diagnosis engine to compute the root causes. Once the root cause has been identified, the diagnosis system takes appropriate actions in order to retain the system’s correct behavior. The fault detection, localization, and correction procedures are all based on declarative models of the control software.