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  4. iCub Joint Space Self-Collision Avoidance [Data & Code]
 
dataset

iCub Joint Space Self-Collision Avoidance [Data & Code]

Koptev, Mikhail  
2021
Zenodo

These data files containg code sources for dataset creation & model learning (Joint-Space-SCA.zip) and collected synthetic dataset of free & collided postures for humanoid robot iCub (raw_binary_data.zip). Follow the Readme.MD files to launch the code if needed. Corresponding Git repo: https://github.com/epfl-lasa/Joint-Space-SCA  

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Type
dataset
DOI
10.5281/zenodo.8387095
Author(s)
Koptev, Mikhail  
Date Issued

2021

Version

1

Publisher

Zenodo

Subjects

Robotics

•

Machine Learning

•

Collision Avoidance

•

iCub

•

Python

•

Matlab

EPFL units
LASA  
FunderGrant NO

EU funding

741945

RelationURL/DOI

IsNewVersionOf

https://zenodo.org/doi/10.5281/zenodo.8387094

IsSupplementTo

https://infoscience.epfl.ch/record/284240
Available on Infoscience
November 3, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/202025
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