Webinaire CeRVIM : Lidar Scan Registration Robust to Extreme Motions
Simon-Pierre Deschênes
Norlab (Northern Robotics Laboratory)
Dép. d’informatique et de génie logiciel, Université Laval
29 avril 2022, 13h
Résumé
Simultaneous Localization And Mapping (SLAM) algorithms based on point cloud registration have proven effective in mobile robotics over the last decades. However, they are susceptible to failure when a robot sustains extreme velocities and accelerations. For example, this type of motion can take place after a collision, causing lidar scans to be heavily skewed. While point cloud de-skewing methods have been explored in the past to increase localization and mapping accuracy, these methods still rely on highly accurate odometry systems or ideal navigation conditions. In this presentation, a new point cloud registration algorithm taking into account the uncertainty left after de-skewing a point cloud will be presented and its performance in a SLAM algorithm will be analyzed.
La présentation sera donnée en anglais et les diapos seront en anglais.
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