Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary

Biao Jia; Zhe Hu; Jia Pan; Dinesh Manocha

doi:10.1109/ICRA.2018.8461264

Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary

Biao Jia^*
, Zhe Hu
, Jia Pan
, Dinesh Manocha^*

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

31 Citations (Scopus)

Abstract

The complex physical properties of highly deformable materials such as clothes pose significant challenges for autonomous robotic manipulation systems. We present a novel visual feedback dictionary-based method for manipulating deformable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.

Original language	English
Title of host publication	2018 IEEE International Conference on Robotics and Automation (ICRA)
Publisher	IEEE
Pages	239-246
ISBN (Electronic)	978-1-5386-3081-5
DOIs	https://doi.org/10.1109/ICRA.2018.8461264
Publication status	Published - May 2018
Event	2018 IEEE International Conference on Robotics and Automation (ICRA 2018) - Brisbane, Australia Duration: 21 May 2018 → 25 May 2018 https://ieeexplore.ieee.org/xpl/conhome/8449910/proceeding

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
Publisher	IEEE
ISSN (Print)	1050-4729
ISSN (Electronic)	2577-087X

Conference

Conference	2018 IEEE International Conference on Robotics and Automation (ICRA 2018)
Abbreviated title	ICRA 2018
Place	Australia
City	Brisbane
Period	21/05/18 → 25/05/18
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8449910/proceeding

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@inproceedings{9c2f31e4ea4c42da95f73522bd011c08,

title = "Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary",

abstract = "The complex physical properties of highly deformable materials such as clothes pose significant challenges for autonomous robotic manipulation systems. We present a novel visual feedback dictionary-based method for manipulating deformable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.",

author = "Biao Jia and Zhe Hu and Jia Pan and Dinesh Manocha",

year = "2018",

month = may,

doi = "10.1109/ICRA.2018.8461264",

language = "English",

series = "Proceedings - IEEE International Conference on Robotics and Automation",

publisher = "IEEE",

pages = "239--246",

booktitle = "2018 IEEE International Conference on Robotics and Automation (ICRA)",

address = "United States",

note = "2018 IEEE International Conference on Robotics and Automation (ICRA 2018), ICRA 2018 ; Conference date: 21-05-2018 Through 25-05-2018",

url = "https://ieeexplore.ieee.org/xpl/conhome/8449910/proceeding",

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Jia, B, Hu, Z , Pan, J & Manocha, D 2018, Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary. in 2018 IEEE International Conference on Robotics and Automation (ICRA)., 8461264, Proceedings - IEEE International Conference on Robotics and Automation, IEEE, pp. 239-246, 2018 IEEE International Conference on Robotics and Automation (ICRA 2018), Brisbane, Queensland, Australia, 21/05/18. https://doi.org/10.1109/ICRA.2018.8461264

Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary. / Jia, Biao; Hu, Zhe ; Pan, Jia et al.
2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. p. 239-246 8461264 (Proceedings - IEEE International Conference on Robotics and Automation).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary

AU - Jia, Biao

AU - Hu, Zhe

AU - Pan, Jia

AU - Manocha, Dinesh

PY - 2018/5

Y1 - 2018/5

N2 - The complex physical properties of highly deformable materials such as clothes pose significant challenges for autonomous robotic manipulation systems. We present a novel visual feedback dictionary-based method for manipulating deformable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.

AB - The complex physical properties of highly deformable materials such as clothes pose significant challenges for autonomous robotic manipulation systems. We present a novel visual feedback dictionary-based method for manipulating deformable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.

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M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - Proceedings - IEEE International Conference on Robotics and Automation

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BT - 2018 IEEE International Conference on Robotics and Automation (ICRA)

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T2 - 2018 IEEE International Conference on Robotics and Automation (ICRA 2018)

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ER -

Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary

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