3 papers
cs.RO2019
Learning Task-Oriented Grasping from Human Activity Datasets
Mia Kokic, Danica Kragic, Jeannette Bohg
We propose to leverage a real-world, human activity RGB dataset to teach a robot Task-Oriented Grasping (TOG). We develop a model that takes as input an RGB image and outputs a han…
cs.CV2019
Learning to Estimate Pose and Shape of Hand-Held Objects from RGB Images
Mia Kokic, Danica Kragic, Jeannette Bohg
We develop a system for modeling hand-object interactions in 3D from RGB images that show a hand which is holding a novel object from a known category. We design a Convolutional Ne…
cs.RO2018
Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation
Rika Antonova, Mia Kokic, Johannes A. Stork +1
We develop an approach that benefits from large simulated datasets and takes full advantage of the limited online data that is most relevant. We propose a variant of Bayesian optim…