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MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map

Authors :
Teddy Ort
Rohan Banerjee
Igor Gilitschenski
Dhaivat Bhatt
Sai Krishna Gottipati
Liam Paull
Krishna Murthy
Daniela Rus
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Source :
Other repository
Publication Year :
2020
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2020.

Abstract

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.

Details

ISSN :
23773774
Volume :
5
Database :
OpenAIRE
Journal :
IEEE Robotics and Automation Letters
Accession number :
edsair.doi.dedup.....07a5d49d1dcbbdc1237b2e369ba41183