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Integration of Multi-sensor Occupancy Grids into Automotive ECUs

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Abstract

Occupancy Grids (OGs) are a popular framework for robotic perception. They were recently adopted for performing multisensor fusion and environment mapping for autonomous vehicles. However, high computational requirements strongly hinder their integration into less powerful automotive ECUs. To overcome this problem, we propose an algorithmic improvement for mapping range measurements into OGs. Experiments were conducted on a vehicle equipped with 16 LIDAR scans. Results demonstrate that a single-core ARM cortex A9 can build now in real-time OGs that map urban traffic scenarios of 100m-by-100m.
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Dates and versions

cea-01518771 , version 1 (05-05-2017)

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Tiana Rakotovao, Julien Mottin, Diego Puschini, Christian Laugier. Integration of Multi-sensor Occupancy Grids into Automotive ECUs. In Proceedings of the 53rd Annual Design Automation Conference (DAC 2016), Jun 2016, Austin, United States. ⟨10.1145/2897937.2898035⟩. ⟨cea-01518771⟩
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