Schreier, Matthias ; Willert, Volker ; Adamy, Jürgen (2014)
Grid Mapping in Dynamic Road Environments: Classification of Dynamic Cell Hypothesis via Tracking.
IEEE International Conference on Robotics and Automation (ICRA). Hong Kong, China (May 31 – June 7)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the representation due to violating the underlying static-world assumptions of common grid mapping algorithms and are therefore detected and filtered from the map. For this purpose, a subsequent step is suggested that identifies, clusters and merges dynamic cell hypothesis in a novel way. Thereafter, an Interacting-Multiple-Model-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) tracker is used to classify of whether cell movements behave consistently with possible movement characteristics of real dynamic objects or are just generated by noise or newly observed static environment. In opposition to many other approaches, the method explicitly combines information of newly occupied and free areas, completes the shape of only partly visible dynamic objects and uses an advanced object tracking scheme to clean the grid from dynamic object corruptions. The method is evaluated with grids generated by an automotive radar and stereo camera in real traffic environments.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Schreier, Matthias ; Willert, Volker ; Adamy, Jürgen |
| Art des Eintrags: | Bibliographie |
| Titel: | Grid Mapping in Dynamic Road Environments: Classification of Dynamic Cell Hypothesis via Tracking |
| Sprache: | Englisch |
| Publikationsjahr: | 24 Juni 2014 |
| Buchtitel: | Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) |
| Veranstaltungstitel: | IEEE International Conference on Robotics and Automation (ICRA) |
| Veranstaltungsort: | Hong Kong, China |
| Veranstaltungsdatum: | May 31 – June 7 |
| Kurzbeschreibung (Abstract): | We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the representation due to violating the underlying static-world assumptions of common grid mapping algorithms and are therefore detected and filtered from the map. For this purpose, a subsequent step is suggested that identifies, clusters and merges dynamic cell hypothesis in a novel way. Thereafter, an Interacting-Multiple-Model-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) tracker is used to classify of whether cell movements behave consistently with possible movement characteristics of real dynamic objects or are just generated by noise or newly observed static environment. In opposition to many other approaches, the method explicitly combines information of newly occupied and free areas, completes the shape of only partly visible dynamic objects and uses an advanced object tracking scheme to clean the grid from dynamic object corruptions. The method is evaluated with grids generated by an automotive radar and stereo camera in real traffic environments. |
| Freie Schlagworte: | PRORETA3 |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme) |
| Hinterlegungsdatum: | 24 Jun 2014 14:00 |
| Letzte Änderung: | 17 Jan 2020 11:28 |
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