Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter
1
Robotics and Embedded Systems, Technische Universität München, Garching bei München, Germany
2
Fortiss GmbH, Guerickestr. 25, München 80805, Germany
*
Author to whom correspondence should be addressed.
Sensors 2014, 14(1), 995-1009; https://doi.org/10.3390/s140100995
Received: 13 November 2013
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Revised: 22 December 2013
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Accepted: 26 December 2013
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Published: 8 January 2014
(This article belongs to the Section Physical Sensors)
This paper studies the problem of multiple vehicle cooperative localization with spatial registration in the formulation of the probability hypothesis density (PHD) filter. Assuming vehicles are equipped with proprioceptive and exteroceptive sensors (with biases) to cooperatively localize positions, a simultaneous solution for joint spatial registration and state estimation is proposed. For this, we rely on the sequential Monte Carlo implementation of the PHD filtering. Compared to other methods, the concept of multiple vehicle cooperative localization with spatial registration is first proposed under Random Finite Set Theory. In addition, the proposed solution also addresses the challenges for multiple vehicle cooperative localization, e.g., the communication bandwidth issue and data association uncertainty. The simulation result demonstrates its reliability and feasibility in large-scale environments.
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Keywords:
random finite set; PHD filter; spatial registration
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This is an open access article distributed under the Creative Commons Attribution License.
MDPI and ACS Style
Zhang, F.; Buckl, C.; Knoll, A. Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter. Sensors 2014, 14, 995-1009. https://doi.org/10.3390/s140100995
AMA Style
Zhang F, Buckl C, Knoll A. Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter. Sensors. 2014; 14(1):995-1009. https://doi.org/10.3390/s140100995
Chicago/Turabian StyleZhang, Feihu, Christian Buckl, and Alois Knoll. 2014. "Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter" Sensors 14, no. 1: 995-1009. https://doi.org/10.3390/s140100995
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