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Extrinsic calibration for highly accurate trajectories reconstruction
Maxime Vaidis, William Dubois, Alexandre Guénette +3
In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long d…
Gravity-constrained point cloud registration
Vladimír Kubelka, Maxime Vaidis, François Pomerleau
Visual and lidar Simultaneous Localization and Mapping (SLAM) algorithms benefit from the Inertial Measurement Unit (IMU) modality. The high-rate inertial data complement the other…
System for multi-robotic exploration of underground environments CTU-CRAS-NORLAB in the DARPA Subterranean Challenge
Tomáš Rouček, Martin Pecka, Petr Čížek +19
We present a field report of CTU-CRAS-NORLAB team from the Subterranean Challenge (SubT) organised by the Defense Advanced Research Projects Agency (DARPA). The contest seeks to ad…
Accurate outdoor ground truth based on total stations
Maxime Vaidis, Philippe Giguère, François Pomerleau +1
In robotics, accurate ground-truth position fostered the development of mapping and localization algorithms through the creation of cornerstone datasets. In outdoor environments an…
Improving the Iterative Closest Point Algorithm using Lie Algebra
Maxime Vaidis, Johann Laconte, Vladimír Kubelka +1
Mapping algorithms that rely on registering point clouds inevitably suffer from local drift, both in localization and in the built map. Applications that require accurate maps, suc…
Evaluation of Skid-Steering Kinematic Models for Subarctic Environments
Dominic Baril, Vincent Grondin, Simon-Pierre Deschênes +6
In subarctic and arctic areas, large and heavy skid-steered robots are preferred for their robustness and ability to operate on difficult terrain. State estimation, motion control…