Prof. Samir Bouaziz Profile

Prof. Samir Bouaziz

at Univ. Paris-Saclay

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Proceedings Article | 7 June 2023 Presentation + Paper

Real-time embedded large-scale place recognition for autonomous ground vehicles using a spatial descriptor

Mohammed Chghaf, Sergio Rodríguez Flórez, Abdelhafid El Ouardi, Samir Bouaziz

Proceedings Volume 12571, 1257104 (2023) https://doi.org/10.1117/12.2664942

KEYWORDS: Field programmable gate arrays, Cameras, Point clouds, LIDAR, Stereoscopic cameras, Sensors, Autonomous vehicles, Data processing, Mathematical optimization, Imaging systems

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Place recognition is a key task in an autonomous vehicle’s Simultaneous Localization and Mapping (SLAM). The motion estimation is bound to drift over time due to cumulative errors. Fortunately, the correct identification of a revisited area provided by the place recognition module enables further optimizations that correct drifting errors if detected in real-time. Place recognition based on structural information of the scene is more robust to luminosity changes that can lead to false detections in the case of feature-based descriptors. However, they were mainly investigated in the context of depth sensors. Inspired by a LiDAR-based descriptor, we extent this global geometric descriptor to structural information from stereo vision system. Using this descriptor, we can achieve real-time place recognition by focusing on the structural appearance of the scene derived from a 3D vision system. First, we introduce the approach used to record the 3D structural information of the visible space based on stereo images. Then, we conduct a parametric optimization protocol for precise place recognition in a given environment. Our experiments on the KITTI dataset show that the proposed approach is comparable to state-of-the-art methods, all while being low-cost. We studied the algorithm’s complexity to propose an optimized parallelization on GPU and SoC architectures. Performance evaluation on different hardware (GeForce RTX 3080, Jetson AGX Xavier, and Arria 10 SoC-FPGA) shows that the real-time requirements of an embedded system are met. Compared to a CPU implementation, processing times showed a speed-up between 4x and 16x, depending on the architecture.

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