Abstract
Event-based strategies for control and estimation can offer great benefits to the field of indoor localisation. They achieve a more efficient use of resources, especially in network communications. In this paper we present the implementation of an event-based state estimator for indoor positioning of a mobile robot. The detection is carried out by a laser scanner attached to a mini-PC, that has not any knowledge of the robot's kinematics. This PC processes the laser data, obtains measurements of the robot position and then decides which samples are transmitted to a remote centre where the event-based estimation is carried out. The decision is made based on the distance between the actual measurement and the predicted position. We tested the performance of different event-based sampling methods and compared them with the periodic sampling. Additionally, we tested how the tuning the noise covariance matrices of the filter influences the estimation accuracy.
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