MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map
Name
MapLite_RAL.pdf
Description
Accepted version
Size
2.87 MB
Format
Adobe PDF
Checksum (MD5)
8f51baa7b869efaaab6979deb39d145e
Author(s)
Ort, Moses Teddy
Murthy, Krishna
Banerjee, Rohan
Gottipati, Sai Krishna
Bhatt, Dhaivat
Gilitschenski, Igor
Paull, Liam
Rus, Daniela L
Date Issued
April 2020
Journal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Ort, Teddy et al. "MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map." IEEE Robotics and Automation Letters 5, 2 (April 2020): 556 - 563.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/lra.2019.2961051
