IEEE Robotics and Automation Letters · 2019 · 21 citations · 32 references
EngineeringAutonomous SystemsRobotics EngineeringAutonomous VehiclesMobile RoboticsPath PlanningAutonomous NavigationIntelligent Transportation SystemsMappingNavigation PlanningNavigation SystemsRobot NavigationAutonomous Vehicle NavigationAutonomous Vehicle Path PlanningIntersectionIntersection NavigationRoad Simulated TestingVehicle Navigation
In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topometric map in order to fuse the high-level navigation goals with a variational path planner in the vehicle frame. This enables the system to plan trajectories that correctly navigate road intersections without the use of an external localization system such as GPS or a detailed prior map. Since the topometric maps already exist for the vast majority of roads, this solution greatly increases the geographical scope for autonomous mobility solutions. We implement MapLite on a full-scale autonomous vehicle and exhaustively test it on over 15 km of road including over 100 autonomous intersection traversals. We further extend these results through simulated testing to validate the system on complex road junction topologies such as traffic circles.
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Raffaelli Charles, Hao Su, Kaichun Mo et al. · 2017 · 9.8K citations
Deep Learning On Graphs (Graphsip Summer School)
Michaël Defferrard · Figshare · 2016 · 5.1K citations
OpenStreetMap: User-Generated Street Maps
Muki Haklay, Patrick Weber · IEEE Pervasive Computing · 2008 · 3.1K citations · Full text