Research Data Leeds Repository

Citation

Hasan, Mohamed and Warburton, Matthew and Agboh, Wisdom C. and Dogar, Mehmet R. and Leonetti, Matteo and Wang, He and Mushtaq, Faisal and Mon-Williams, Mark and Cohn, Anthony G. (2020) Learning manipulation planning from VR human demonstrations. University of Leeds. [Dataset] https://doi.org/10.5518/780

Dataset description

The objective of this project is learning high-level manipulation planning skills from humans and transfer these skills to robot planners. We used virtual reality to generate data from human participants whilst they reached for objects on a cluttered table top. From this, we devised a qualitative representation of the task space to abstract human decisions, irrespective of the number of objects in the way. Based on this representation, human demonstrations were segmented and used to train decision classifiers. Using these classifiers, our planner produced a list of waypoints in the task space. These waypoints provide a high-level plan, which can be transferred to any arbitrary robot model. The VR dataset is released here.

Subjects:	H000 - Engineering > H600 - Electronic & electrical engineering > H670 - Robotics & cybernetics > H671 - Robotics I000 - Computer sciences > I400 - Artificial intelligence > I460 - Machine learning C000 - Biological sciences > C800 - Psychology H000 - Engineering > H600 - Electronic & electrical engineering > H670 - Robotics & cybernetics > H674 - Virtual reality engineering
Divisions:	Faculty of Engineering and Physical Sciences > School of Computing
Related resources:	Location Type https://arxiv.org/abs/2002.12738 Publication https://doi.org/10.1109/ICRA40945.2020.9196665 Publication http://eprints.whiterose.ac.uk/158051/ Publication https://artificial-intelligence.leeds.ac.uk/human-like-computing/ Website
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	01 May 2020 11:05
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/664
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Hasan, Mohamed https://orcid.org/0000-0002-7477-7133 University of Leeds https://ror.org/024mrxd33 ror Warburton, Matthew https://orcid.org/0000-0001-5309-4424 University of Leeds https://ror.org/024mrxd33 ror Agboh, Wisdom C. https://orcid.org/0000-0002-0242-0215 University of Leeds https://ror.org/024mrxd33 ror Dogar, Mehmet R. https://orcid.org/0000-0002-6896-5461 University of Leeds https://ror.org/024mrxd33 ror Leonetti, Matteo https://orcid.org/0000-0002-3831-2400 University of Leeds https://ror.org/024mrxd33 ror Wang, He https://orcid.org/0000-0002-2281-5679 University of Leeds https://ror.org/024mrxd33 ror Mushtaq, Faisal https://orcid.org/0000-0001-7881-1127 University of Leeds https://ror.org/024mrxd33 ror Mon-Williams, Mark https://orcid.org/0000-0001-7595-8545 University of Leeds https://ror.org/024mrxd33 ror Cohn, Anthony G. https://orcid.org/0000-0002-7652-8907 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: EPSRC Grant numbers: EP/R031193/1 Publication date: 2020 Resource language: English Metadata language: English Research project title: Humanlike physics understanding for autonomous robots Publisher: University of Leeds Contact email: m.hasan@leeds.ac.uk Last Modified: 23 Jul 2024 09:13

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Data

Participants [825B] Participants [825B] Participants [825B] Security: Anyone File name: participant_list.csv Content type: Data Mime-Type: text/csv License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 825B

hlp-VR-dataset.zip [201MB] hlp-VR-dataset.zip [201MB] hlp-VR-dataset.zip [201MB] Security: Anyone File name: hlp-VR-dataset.zip Content type: Data Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 201MB

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