Integration of Multi-sensor Occupancy Grids into Automotive ECUs

Tiana Rakotovao; Julien Mottin; Diego Puschini; Christian Laugier

Integration of Multi-sensor Occupancy Grids into Automotive ECUs

Tiana Rakotovao ^{1, 2} Julien Mottin ¹ Diego Puschini ¹ Christian Laugier ²

1 CEA-LETI - Laboratoire d'Electronique et des Technologies de l'Information

2 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques

CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Grenoble - Rhône-Alpes

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.

Keywords : perception sensor fusion embedded integration environment model

Document type :

Conference papers

Domain :

Computer Science [cs] / Robotics [cs.RO]

Complete list of metadatas

https://hal-cea.archives-ouvertes.fr/cea-01518771
Contributor : Tiana Rakotovao <>
Submitted on : Friday, May 5, 2017 - 1:45:18 PM
Last modification on : Friday, June 21, 2019 - 9:51:45 AM

Integration of Multi-sensor Occupancy Grids into Automotive ECUs

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Integration of Multi-sensor Occupancy Grids into Automotive ECUs

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