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AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking Lot
[article]
2020
arXiv
pre-print
Autonomous valet parking is a specific application for autonomous vehicles. In this task, vehicles need to navigate in narrow, crowded and GPS-denied parking lots. Accurate localization ability is of great importance. Traditional visual-based methods suffer from tracking lost due to texture-less regions, repeated structures, and appearance changes. In this paper, we exploit robust semantic features to build the map and localize vehicles in parking lots. Semantic features contain guide signs,
arXiv:2007.01813v2
fatcat:6l53fbk6gfa5dbdc7xaomm5ooy