Multi-Vehicle Cooperative Local Mapping: A Methodology Based on Occupancy Grid Map Merging

Abstract : Local mapping is valuable for many real-time applications of intelligent vehicle systems. Multi-vehicle cooperative local mapping can bring considerable benefits for vehicles operating in some challenging scenarios. In this paper, we introduce a method of occupancy grid map merging, dedicated to multi-vehicle cooperative local mapping purpose in outdoor environment. 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 relative pose estimation, which can serve as a general solution for multi-vehicle 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 vehicle-to-vehicle relative pose estimation strategy.
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Hao Li, Manabu Tsukada, Fawzi Nashashibi, Michel Parent. Multi-Vehicle Cooperative Local Mapping: A Methodology Based on Occupancy Grid Map Merging. IEEE Transactions on Intelligent Transportation Systems, IEEE, 2014, 15 (5), pp.12. ⟨10.1109/TITS.2014.2309639⟩. ⟨hal-01107534⟩

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