A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation

Related tags

Deep Learningdlm
Overview

A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation

This repository contains the source code of the paper A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation, CoRL 2021.

Content

The code contains five sets of experiments:

1. Fully connneced Neural Network Trained on robot actions (Exp_NN)
2. Fully connneced Neural Network Trained on differnetiable simulator (Exp_NNM)
3. Differentiable Pipaline Trained on machanical parameters (Exp_MDR)
4. Differentiable Pipaline Trained on machanical parameters and CVX Layer (Exp_CVX)
5. Differentiable Pipaline Trained on end to end with simulation (Exp_DLM)

Installation

Install the dependencies:

  1. Pytorch 1.4.0 (https://pytorch.org/)
  2. CVXPy Layers (https://github.com/cvxgrp/cvxpylayers)
  3. PyGame (https://www.pygame.org/wiki/GettingStarted)
  4. PyODE (http://pyode.sourceforge.net/)

To install the simulator, also install:

cd ./src/diffsim_lcp
python setup.py install --user

Tested in Python 3.7.7

Citing

If you find this repository helpful in your publications, please cite the following:

@inproceedings{aceituno2021corl,
    title={A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation },
    author={B. Aceituno, and A. Rodriguez, and S. Tulsiani, and A. Gupta, and M. Mukadam},
    booktitle={CoRL},
    year={2021}
}

License

This repository is licensed under the MIT License.

Owner
Bernardo Aceituno
Graduate Student at the Massachusetts Institute of Technology (MIT).
Bernardo Aceituno
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans

Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap

Photogrammetry & Robotics Bonn 40 Dec 01, 2022
GNN-based Recommendation Benchmark

GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma

73 Oct 17, 2022
A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild"

VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video

45 Nov 29, 2022
A trashy useless Latin programming language written in python.

Codigum! The first programming langage in latin! (please keep your eyes closed when if you read the source code) It is pretty useless though. Document

Bic 2 Oct 25, 2021
Code for the paper "Curriculum Dropout", ICCV 2017

Curriculum Dropout Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability dis

Pietro Morerio 21 Jan 02, 2022
This repository introduces a short project about Transfer Learning for Classification of MRI Images.

Transfer Learning for MRI Images Classification This repository introduces a short project made during my stay at Neuromatch Summer School 2021. This

Oscar Guarnizo 3 Nov 15, 2022
PyTorch package for the discrete VAE used for DALL·E.

Overview [Blog] [Paper] [Model Card] [Usage] This is the official PyTorch package for the discrete VAE used for DALL·E. Installation Before running th

OpenAI 9.5k Jan 05, 2023
Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

Packt 1.5k Jan 03, 2023
Graduation Project

Gesture-Detection-and-Depth-Estimation This is my graduation project. (1) In this project, I use the YOLOv3 object detection model to detect gesture i

ChaosAT 1 Nov 23, 2021
TensorFlow implementation of ENet, trained on the Cityscapes dataset.

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

Fredrik Gustafsson 248 Dec 16, 2022
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

David Álvarez de la Torre 1 Dec 02, 2022
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

Jialian Wu 54 Jan 06, 2023
Blind Video Temporal Consistency via Deep Video Prior

deep-video-prior (DVP) Code for NeurIPS 2020 paper: Blind Video Temporal Consistency via Deep Video Prior PyTorch implementation | paper | project web

Chenyang LEI 272 Dec 21, 2022
Reproduces the results of the paper "Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations".

Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo

Ben Moseley 65 Dec 28, 2022
Python binding for Khiva library.

Khiva-Python Build Documentation Build Linux and Mac OS Build Windows Code Coverage README This is the Khiva Python binding, it allows the usage of Kh

Shapelets 46 Oct 16, 2022
Code repo for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper.

InterpretableMDE A PyTorch implementation for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper. arXiv link: https://arxiv.or

Zunzhi You 16 Aug 12, 2022
WiFi-based Multi-task Sensing

WiFi-based Multi-task Sensing Introduction WiFi-based sensing has aroused immense attention as numerous studies have made significant advances over re

zhangx289 6 Nov 24, 2022
OpenDILab RL Kubernetes Custom Resource and Operator Lib

DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w

OpenDILab 205 Dec 29, 2022
Improving Transferability of Representations via Augmentation-Aware Self-Supervision

Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor

hankook 38 Sep 16, 2022
LRBoost is a scikit-learn compatible approach to performing linear residual based stacking/boosting.

LRBoost is a sckit-learn compatible package for linear residual boosting. LRBoost combines a linear estimator and a non-linear estimator to leverage t

Andrew Patton 5 Nov 23, 2022