Kuka, Christian and Gerwinn, Sebastian and Schweigert, Sören and Eilers, Sönke and Nicklas, Daniela
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Autonomously operating vehicles highly depend on the qual-ity of its sensors as they have to be aware of its surround-ings to react appropriately. Currently operating automatedguided vehicles cover only a limited area with their sensorsand therefore can only drive at low speeds. However, asmore and more sensors are available, it is essential to builda context-model, which fuses information of diﬀerent sen-sors to cover a larger area and allow for an increased levelof autonomy. In this paper, we present a context-modelbased on a Bayesian occupancy ﬁlter which can be queriedvia a data stream management system in order to providethe necessary information at any point in time. Addition-ally, the Bayesian ﬁlter is pessimistically as it is constructedsuch that probability of occupancy is always upper bounded,to ensure a suﬃcient level of safety.
07 / 2012
SaLsA Sichere autonome Logistik- und Transportfahrzeuge im Außenbereich