Multivehicle Cooperative Local Mapping: A Methodology Based on Occupancy Grid Map Merging

Local mapping is valuable for many real-time applications of intelligent vehicle systems. Multivehicle cooperative local mapping can bring considerable benefits to vehicles operating in some challenging scenarios. In this paper, we introduce a method of occupancy grid map merging, dedicated to multi...

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Veröffentlicht in:IEEE Transactions on Intelligent Transportation Systems Jg. 15; H. 5; S. 2089 - 2100
Hauptverfasser: Hao Li, Tsukada, Manabu, Nashashibi, Fawzi, Parent, Michel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2014
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
[SPI.AUTO] Engineering Sciences [physics]/Automatic
Cooperative local mapping
Cooperative perception
Estimation
Feature extraction
Global Positioning System
Intelligent transportation systems
intelligent vehicle systems
Intelligent vehicles
Linear programming
map merging
Mapping
Merging
occupancy grid map
Optimization
Outdoor
Perception
relative pose (RP) estimation
relative pose estimation
Simultaneous localization and mapping
Strategy
Vehicles
map merging
relative pose (RP) estimation
Cooperative local mapping
intelligent vehicle systems
cooperative perception
occupancy grid map
ISSN:1524-9050, 1558-0016
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Zusammenfassung:Local mapping is valuable for many real-time applications of intelligent vehicle systems. Multivehicle cooperative local mapping can bring considerable benefits to vehicles operating in some challenging scenarios. In this paper, we introduce a method of occupancy grid map merging, dedicated to multivehicle cooperative local mapping purpose in outdoor environments. In a general map merging framework, we propose an objective function based on occupancy likelihood and provide some concrete procedures designed in the spirit of genetic algorithm to optimize the defined objective function. Based on the introduced method, we further describe a strategy of indirect vehicle-to-vehicle (V2V) relative pose (RP) estimation, which can serve as a general solution for multivehicle perception association. We present a variety of experiments that validate the effectiveness of the proposed occupancy grid map merging method. We also demonstrate several useful application examples of the indirect V2V RP estimation strategy.
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ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2014.2309639