Extending occupancy grid mapping for dynamic environments

Joseph Wessner, Wolfgang Utschick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In this paper, the commonly used filtering technique occupancy grid mapping for static environments is extended for dynamic environments. The proposed method is able to estimate velocities indirectly. We apply a distribution model of the respective state variable to estimate the cell dynamics by means of prediction and update cycle, as known by standard tracking filters. Therefore, we present a straight forward derivation of the prediction and update rule. Furthermore, we validate our approach by simple one dimensional simulations, and show how it can be extended into a two dimensional world, including the resulting consequences, e.g. in terms of memory requirements.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Vehicles Symposium, IV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages701-707
Number of pages7
ISBN (Electronic)9781538644522
DOIs
StatePublished - 18 Oct 2018
Event2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, China
Duration: 26 Sep 201830 Sep 2018

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2018-June

Conference

Conference2018 IEEE Intelligent Vehicles Symposium, IV 2018
Country/TerritoryChina
CityChangshu, Suzhou
Period26/09/1830/09/18

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