The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/60422807-0525-4cf5-a18f-f6aa6dd0b048

Bombile, Michael; Billard, Aude (2023): I.AM. archive containing recordings of dual-arm grabbing and tossing onto a target moving on a conveyor belt for learning and control. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/60422807-0525-4cf5-a18f-f6aa6dd0b048.v1

Dataset

• Interdisciplinary Engineering
• Engineering

Collision, Grab, Impact, Impact-Aware Manipulation, Learning, Object, Robotics, Toss

CC BY-NC-SA 4.0

• Impact-Aware Robotics Archives Collection

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Michael Bombile , Aude Billard

I.AM. archive as part of the Impact-Aware Robotics Archives Collection.

This archive contains recordings of experiments that are executed under the scenario of GRAB. In these recordings, two LBR IIWA robots are used to grab and toss Box013 and Box014 on a conveyor belt. The purpose of these experiments is to obtain data that validates not only the effectiveness but also the speed and energy advantages of using dynamic grabbing and releasing of objects (using Impact and tossing) in comparison to the traditional picking and placing strategy.

All the recordings in the archive were performed at the Learning Algorithm and System Laboratory (LASA) ,

located within the EPFL campus.

• 2023-10-05 first online, published, posted

4TU.ResearchData

HDF5

Bimanual dynamic grabbing and tossing of objects onto a moving target, Robotics and Autonomous Systems

• https://www.sciencedirect.com/science/article/pii/S0921889023001203

Ecole Polytechnique Fédérale de Lausanne, Learning Algorithm and System Laboratory