5 papers
A Coordinate-Invariant Local Representation of Motion and Force Trajectories for Identification and Generalization Across Coordinate Systems
Arno Verduyn, Erwin Aertbeliën, Maxim Vochten +1
Identifying the trajectories of rigid bodies and of interaction forces is essential for a wide range of tasks in robotics, biomechanics, and related domains. These tasks include tr…
Enhancing Hand Palm Motion Gesture Recognition by Eliminating Reference Frame Bias via Frame-Invariant Similarity Measures
Arno Verduyn, Maxim Vochten, Joris De Schutter
The ability of robots to recognize human gestures facilitates a natural and accessible human-robot collaboration. However, most work in gesture recognition remains rooted in refere…
BILTS: A Bi-Invariant Similarity Measure for Robust Object Trajectory Recognition under Reference Frame Variations
Arno Verduyn, Erwin Aertbeliën, Glenn Maes +2
When similar object motions are performed in diverse contexts but are meant to be recognized under a single classification, these contextual variations act as disturbances that neg…
Automatic Derivation of an Optimal Task Frame for Learning and Controlling Contact-Rich Tasks
Ali Mousavi Mohammadi, Maxim Vochten, Erwin Aertbeliën +1
In previous work on learning and controlling contact-rich tasks, the procedure for choosing a proper reference frame to express learned signals for the motion and the interaction w…
Enhancing motion trajectory segmentation of rigid bodies using a novel screw-based trajectory-shape representation
Arno Verduyn, Maxim Vochten, Joris De Schutter
Trajectory segmentation refers to dividing a trajectory into meaningful consecutive sub-trajectories. This paper focuses on trajectory segmentation for 3D rigid-body motions. Most…