57 citations · 71 across the 7 of their papers we have counts for
16 papers
Tree Detection and Diameter Estimation Based on Deep Learning
Vincent Grondin, Jean-Michel Fortin, François Pomerleau +1
Tree perception is an essential building block toward autonomous forestry operations. Current developments generally consider input data from lidar sensors to solve forest navigati…
Training Deep Learning Algorithms on Synthetic Forest Images for Tree Detection
Vincent Grondin, François Pomerleau, Philippe Giguère
Vision-based segmentation in forested environments is a key functionality for autonomous forestry operations such as tree felling and forwarding. Deep learning algorithms demonstra…
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…