no code implementations • 28 Sep 2023 • Frederik Hagelskjær, Kasper Høj Lorenzen, Dirk Kraft
Our set-up is tested on the World Robot Summit 2018 Assembly Challenge and successfully obtains a higher score compared with all teams at the competition.
no code implementations • 28 Mar 2023 • Frederik Hagelskjær, Rasmus Laurvig Haugaard
In this paper, we present KeyMatchNet, a novel network for zero-shot pose estimation in 3D point clouds.
no code implementations • 9 Mar 2023 • Rasmus Laurvig Haugaard, Frederik Hagelskjær, Thorbjørn Mosekjær Iversen
Pose estimation is usually approached by seeking the single best estimate of an object's pose, but this approach is ill-suited for tasks involving visual ambiguity.
no code implementations • 19 Dec 2019 • Frederik Hagelskjær, Anders Glent Buch
We present a learning-based method for 6 DoF pose estimation of rigid objects in point cloud data.