@inproceedings{589c0b77f8af4cbebd9777a9b23ec166,
title = "Demonstrating cloth folding to robots: design and evaluation of a 2D and a 3D user interface",
abstract = "An appropriate user interface to collect human demonstration data for deformable object manipulation has been mostly overlooked in the literature. We present an inter-action design for demonstrating cloth folding to robots. Users choose pick and place points on the cloth and can preview a visualization of a simulated cloth before real-robot execution. Two interfaces are proposed: A 2D display-and-mouse interface where points are placed by clicking on an image of the cloth, and a 3D Augmented Reality interface where the chosen points are placed by hand gestures. We conduct a user study with 18 participants, in which each user completed two sequential folds to achieve a cloth goal shape. Results show that while both interfaces were acceptable, the 3D interface was more suitable for understanding the task, and the 2D interface was suitable for repetition. Results also found that fold previews improve three key metrics: task efficiency, the ability to predict the final shape of the cloth, and overall user satisfaction.",
author = "Benjamin Waymouth and Akansel Cosgun and Rhys Newbury and Tin Tran and Chan, \{Wesley P.\} and Tom Drummond and Elizabeth Croft",
note = "Funding Information: VII. ACKNOWLEDGEMENT This project was supported by the Australian Research Council (ARC) Discovery Project Grant DP200102858. REFERENCES [1] O. Kroemer, S. Niekum, and G. Konidaris, “A review of robot learning for manipulation: Challenges, representations, and algorithms,” Jour-nal of Machine Learning Research, vol. 22, pp. 30:1–30:82, 2021. [2] W. P. Chan, G. Hanks, M. Sakr, T. Zuo, H. Machiel Van der Loos, and E. Croft, “An augmented reality human-robot physical collaboration interface design for shared, large-scale, labour-intensive manufacturing tasks,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, pp. 11 308–11 313. [3] J. Schulman, J. Ho, C. Lee, and P. Abbeel, “Generalization in robotic manipulation through the use of non-rigid registration,” in Proceedings of the 16th International Symposium on Robotics Research (ISRR), 2013. [4] S. Miller, J. Van Den Berg, M. Fritz, T. Darrell, K. Goldberg, and P. Abbeel, “A geometric approach to robotic laundry folding,” The International Journal of Robotics Research, vol. 31, pp. 249 – 267, 2012. [5] M. Laskey, C. Powers, R. Joshi, A. Poursohi, and K. Goldberg, “Learning robust bed making using deep imitation learning with dart,” ArXiv, vol. abs/1711.02525, 2017. [6] J. Sanchez, J.-A. Corrales, B.-C. Bouzgarrou, and Y. Mezouar, “Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey,” The International Journal of Robotics Research, vol. 37, no. 7, pp. 688–716, 2018. [7] J. Maitin-Shepard, M. Cusumano-Towner, J. Lei, and P. Abbeel, “Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding,” in 2010 IEEE International Conference on Robotics and Automation, 2010, pp. 2308–2315. [8] R. Lee, D. Ward, A. Cosgun, V. Dasagi, P. Corke, and J. Leitner, “Learning arbitrary-goal fabric folding with one hour of real robot experience,” Conference on Robot Learning (CoRL), 2020. [9] Y. Wu, W. Yan, T. Kurutach, L. Pinto, and P. Abbeel, “Learning to manipulate deformable objects without demonstrations,” 2020. [10] Y. Tsurumine, Y. Cui, K. Yamazaki, and T. Matsubara, “Generative adversarial imitation learning with deep p-network for robotic cloth manipulation,” in 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), 2019, pp. 274–280. [11] J. Matas, S. James, and A. J. Davison, “Sim-to-real reinforcement learning for deformable object manipulation,” in Conference on Robot Learning (CoRL), vol. abs/1806.07851, 2018. Publisher Copyright: {\textcopyright} 2021 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; IEEE/RSJ International Symposium on Robot and Human Interactive Communication 2021, RO-MAN 2021 ; Conference date: 08-08-2021 Through 12-08-2021",
year = "2021",
doi = "10.1109/RO-MAN50785.2021.9515469",
language = "English",
isbn = "9781665446372",
series = "2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
pages = "155--160",
editor = "Silvia Rossi and Harold Soh",
booktitle = "30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021",
address = "United States of America",
url = "https://ieeexplore.ieee.org/xpl/conhome/9515344/proceeding, https://ro-man2021.org/",
}