DORMADL - Dataset of Human-Operated Robot Arm Motion in Activities of Daily Living
Felix Goldau, Yashaswini Shivashankar, Annalies Baumeister, Lennart Drescher, Patrizia Tolle, Udo Frese
Abstract
This work presents a dataset of human-operated robot motion to be used within the context of assistive robotics and assorted fields, such as learning from demonstrations, machine-learning based robot control, and activity recognition. The data consists of individual sequences of intentional robot motion performing a task in an environment of daily living. There are 2973 sequences generated in a high-resolution simulation and 986 sequences performed in reality, totaling to 1.16 M datapoints. The data includes labels for the robot's pose, motion and activity. This paper also provides data augmentation methods and a detailed dataset analysis as well as simple models trained on the dataset as a baseline for future research. The dataset can be downloaded free-of-charge at https://www.kaggle.com/f371xx/dormadl.
BibTeX
@inproceedings{iros2023_dormadldatasetof,
title = {DORMADL - Dataset of Human-Operated Robot Arm Motion in Activities of Daily Living},
author = {Felix Goldau and Yashaswini Shivashankar and Annalies Baumeister and Lennart Drescher and Patrizia Tolle and Udo Frese},
booktitle = {IROS 2023},
year = {2023}
}