Autonomous Navigation in Inclement Weather based on a Localizing Ground Penetrating Radar
Author(s)
Ort, Teddy; Gilitschenski, Igor; Rus, Daniela
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Most autonomous driving solutions require some method of localization within their environment. Typically, onboard sensors are used to localize the vehicle precisely in a previously recorded map. However, these solutions are sensitive to ambient lighting conditions such as darkness and inclement weather. Additionally, the maps can become outdated in a rapidly changing environment and require continuous updating. While LiDAR systems don't require visible light, they are sensitive to weather such as fog or snow, which can interfere with localization. In this letter, we utilize a Ground Penetrating Radar (GPR) to obtain precise vehicle localization. By mapping and localizing using features beneath the ground, we obtain features that are both stable over time, and maintain their appearance during changing ambient weather and lighting conditions. We incorporate this solution into a full-scale autonomous vehicle and evaluate the performance on over 17 km of testing data in a variety of challenging weather conditions. We find that this novel sensing modality is capable of providing precise localization for autonomous navigation without using cameras or LiDAR sensors.
Date issued
2020Department
Lincoln Laboratory; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)