Robot Learning of Assembly Tasks from Non-expert Demonstrations using Functional Object-Oriented Network

TL;DR – This was a collaboration with Clemson University’s Yunyi Jia and Yi Chen, who were interested in using FOONs for representing assembly tasks. They successfully utilized and adapted a FOON to robotic assembly execution.

July 2022 · Yi Chen, David Paulius, Yu Sun, Yunyi Jia

Estimating Motion Codes from Demonstration Videos

TL;DR – In this work, we showed how motion codes (which can be constructed using the motion taxonomy proposed in our RSS 2020 paper) can be used to improve action recognition with deep neural networks.

January 2021 · Maxat Alibayev, David Paulius, Yu Sun

A Motion Taxonomy for Manipulation Embedding

TL;DR – In this work, we introduce new changes to the features of the motion taxonomy and show how action verbs encoded as motion codes better capture differences between them than conventional word embedding (as word2vec).

July 2020 · David Paulius, Nicholas Eales, Yu Sun

Manipulation Motion Taxonomy and Coding for Robots

TL;DR – This paper introduces the motion taxonomy, a collection of robot-relevant features that are better suited for verb or action embedding than conventional word embedding. Motion codes are constructed per verb using the taxonomy. In this work, we show that motion codes assigned to verbs are closely related to one another based on force and trajectory data.

November 2019 · David Paulius, Yongqiang Huang, Jason Meloncon, Yu Sun