1. Vision-based Robot Localization Across Seasons and in Remote Locations
Anirudh Viswanathan, Bernardo Pires, and Daniel Huber
The Robotics Institute, Carnegie Mellon University, USA
GPS-denied unmanned ground vehicle (UGV) localization by matching ground images to a satellite map
Maps captured in different seasons of the year exhibit high variation in appearance caused by changes in vegetation, etc.
Image-matching using semantic information, invariant to seasonal change, is used to localize the UGV
Localization across seasons is demonstrated for maps captured in spring, summer, and winter
Localizing ground-based panorama to maps captured in different seasons