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  4. Neural Joint Space Implicit Signed Distance Functions [Data & Code]
 
dataset

Neural Joint Space Implicit Signed Distance Functions [Data & Code]

Koptev, Mikhail  
2022
Zenodo

These data files containg code sources for dataset creation & model learning (neural-jsdf.zip) and collected synthetic dataset of free & collided postures for robotic arm Franka (sdf_3m_full_mesh.mat). Follow the Readme.MD files to launch the code if needed. Corresponding Git repo: https://github.com/epfl-lasa/Neural-JSDF

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Type
dataset
DOI
10.5281/zenodo.8387165
ACOUA ID

1b6a7ca3-be1d-406d-aef0-2eaa7ae463f6

Author(s)
Koptev, Mikhail  
Date Issued

2022

Version

1

Publisher

Zenodo

Subjects

Robotics

•

Machine Learning

•

Collision Avoidance

•

Neural Networks

•

Python

•

Matlab

FunderGrant NO

EU funding

741945

RelationURL/DOI

IsNewVersionOf

https://zenodo.org/doi/10.5281/zenodo.8387164

IsSupplementTo

https://infoscience.epfl.ch/record/299201
Available on Infoscience
November 3, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/202026
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