Redundant Multi-Object Detection for Autonomous Vehicles in Structured Environments

Redundant Multi-Object Detection for Autonomous Vehicles in Structured Environments

This paper presents a redundant multi-object detection method for autonomous driving, exploiting a combination of Light Detection and Ranging (LiDAR) and stereocamera sensors to detect different obstacles. These sensors are used for distinct perception pipelines considering a custom hardware/softwar...

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Bibliographic Details
Main Authors: Stefano Feraco, Angelo Bonfitto, Nicola Amati, Andrea Tonoli
Format: Article
Language:English
Published: University of Žilina 2022-01-01
Series:Communications
Subjects:
perception
autonomous driving
obstacle detection
point-cloud segmentation
single shot detector
lidar (light detection and ranging)
Online Access:https://komunikacie.uniza.sk/artkey/csl-202201-0009_redundant-multi-object-detection-for-autonomous-vehicles-in-structured-environments.php

Internet

https://komunikacie.uniza.sk/artkey/csl-202201-0009_redundant-multi-object-detection-for-autonomous-vehicles-in-structured-environments.php

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