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Form2Fit

Code for the paper

Form2Fit: Learning Shape Priors for Generalizable Assembly from Disassembly
Kevin Zakka, Andy Zeng, Johnny Lee, Shuran Song
arxiv.org/abs/1910.13675
ICRA 2020

Drawing

This repository contains:

  • The Form2Fit Benchmark
  • Code to reproduce the paper results:
    • Architectures, dataloaders and losses for suction, place and matching networks.
    • Planner module for intergrating all the outputs.
    • Baseline implementation.

If you find this code useful, consider citing our work:

@inproceedings{zakka2020form2fit,
  title={Form2Fit: Learning Shape Priors for Generalizable Assembly from Disassembly},
  author={Zakka, Kevin and Zeng, Andy and Lee, Johnny and Song, Shuran},
  booktitle={Proceedings of the IEEE International Conference on Robotics and Automation},
  year={2020}
}

Documentation

Todos

  • Add processed generalization partition (combinations, mixtures and unseen) to benchmark.
  • Add code for training the different networks.

Note

This is not an officially supported Google product.

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[ICRA 2020] Train generalizable policies for kit assembly with self-supervised dense correspondence learning.

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