A sensor failure detection framework for autonomous mobile robots

This paper presents a failure detection framework for external sensors on autonomous mobile robots. Each sensor's measurements make statements about the robot's environment. Whereas correctly functioning sensors' statements are consistent, the readings of faulty sensors will lead to inconsistencies within the robot's model of the environment. A probabilistic formulation of both the sensor model and the statements about the environment allows for a quantitative examination of these inconsistencies. The obtained consistency measure describes how well a statement, corresponding to a reading of a single sensor matches with the statements generated by the measurements of all other sensors. By combining a sensor's consistency measures over several statements, the robot is able to deliberate about the condition of this sensor. The approach provides a mechanism, which is suitable for any unknown environment and is flexible in terms of failure and sensor types. It was verified by several experiments with the autonomous mobile robot ROAMER, using sonar readings integrated into a probabilistic occupancy grid representation.

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