Abstract
IAV developed a novel data fusion approach to ensure a comprehensive environmental perception for the autonomous driving in urban environments. The approach is highly scalable, easily adaptable, and sensor independent while processing heterogeneous data. It is based on a dynamic occupancy grid in conjunction with a sophisticated combination of inverse sensor models which are taking the sensor properties into account. The approach has been successfully used within the HEAT project and will be discussed in this context.
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© 2021 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Materne, P., Hartwig, C., Peters, U. (2021). HEAT as an example for efficient environmental perception for autonomous shuttle systems. In: Bertram, T. (eds) Automatisiertes Fahren 2021. Proceedings. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-34754-3_1
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DOI: https://doi.org/10.1007/978-3-658-34754-3_1
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