3 accepted papers
Estimating the pose of an object is essential for robot manipulation. In many applications the spatial and geometric relations between the object and the other parts of the world, e.g. the relation between the object and its supporting plane, are a-priori known or can be assumed with a certain accur
In this paper, we investigate the problems that Convolutional Neural Networks (CNN)-based pose estimators have with symmetric objects. We considered the value of the CNN’s output representation when continuously rotating the object and found that it has to form a closed loop after each step of symme…
We present a new dataset with the goal of advancing the state-of-the-art in object pose estimation especially for stored porcelain and glass crockery in kitchen scenes. Specifically the ESKO 6d (EASE Stored Kitchen Objects with 6d poses) dataset features texture-less, glossy or glassy ordinary used…