Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit

Related tags

Deep Learningstorm
Overview

STORM

Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit

[Install Instructions] [Paper] [Website]

This package contains code for reactive robot motion leveraging parallel compute on the GPU. The implemented control framework leverages MPPI to optimize over sampled actions and their costs. The costs are computed by rolling out the forward model from the current state with the sampled actions.

Most files are documented with sphinx. Once you clone this repo, go into docs folder and run sh generate_docs.sh to generate documentation.

Citation

If you use this source code, please cite the below article,

@article{storm2021,
  title={Fast Joint Space Model-Predictive Control for Reactive Manipulation},
  author={Mohak Bhardwaj and Balakumar Sundaralingam and Arsalan Mousavian and Nathan Ratliff and Dieter Fox and Fabio Ramos and Byron Boots},
  journal={arXiv preprint},
  year={2021}
}

Contributing to this code

Refer to CLA before making contributions.

Owner
NVIDIA Research Projects
NVIDIA Research Projects
Medical Image Segmentation using Squeeze-and-Expansion Transformers

Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im

askerlee 172 Dec 20, 2022
Solutions and questions for AoC2021. Merry christmas!

Advent of Code 2021 Merry christmas! 🎄 🎅 To get solutions and approximate execution times for implementations, please execute the run.py script in t

Wilhelm Ã…gren 5 Dec 29, 2022
A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks incl

Max 65 Dec 09, 2022
PyTorch implementation of SmoothGrad: removing noise by adding noise.

SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro

SSKH 143 Jan 05, 2023
Research shows Google collects 20x more data from Android than Apple collects from iOS. Block this non-consensual telemetry using pihole blocklists.

pihole-antitelemetry Research shows Google collects 20x more data from Android than Apple collects from iOS. Block both using these pihole lists. Proj

Adrian Edwards 290 Jan 09, 2023
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

JiaKui Hu 10 Oct 28, 2022
A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022
Small little script to scrape, parse and check for active tor nodes. Can be used as proxies.

TorScrape TorScrape is a small but useful script made in python that scrapes a website for active tor nodes, parse the html and then save the nodes in

5 Dec 04, 2022
SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals

SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals Abstract Sleep apnea (SA) is a common slee

9 Dec 21, 2022
(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"

(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"

xxxnell 656 Dec 30, 2022
Prompt-BERT: Prompt makes BERT Better at Sentence Embeddings

Prompt-BERT: Prompt makes BERT Better at Sentence Embeddings Results on STS Tasks Model STS12 STS13 STS14 STS15 STS16 STSb SICK-R Avg. unsup-prompt-be

196 Jan 08, 2023
Hardware accelerated, batchable and differentiable optimizers in JAX.

JAXopt Installation | Examples | References Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX. Installation JAXopt can be

Google 621 Jan 08, 2023
PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models

Maximum Entropy Generators for Energy-Based Models All experiments have tensorboard visualizations for samples / density / train curves etc. To run th

Rithesh Kumar 135 Oct 27, 2022
Python library to receive live stream events like comments and gifts in realtime from TikTok LIVE.

TikTokLive A python library to connect to and read events from TikTok's LIVE service A python library to receive and decode livestream events such as

Isaac Kogan 277 Dec 23, 2022
Sparse-dense operators implementation for Paddle

Sparse-dense operators implementation for Paddle This module implements coo, csc and csr matrix formats and their inter-ops with dense matrices. Feel

北海若 3 Dec 17, 2022
Explanatory Learning: Beyond Empiricism in Neural Networks

Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets

GLADIA Research Group 10 Dec 06, 2022
Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.

PHDimGeneralization Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021. Overvie

Tolga Birdal 13 Nov 08, 2022
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation

Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo

Zayd Hammoudeh 2 Oct 08, 2022
Multi-Output Gaussian Process Toolkit

Multi-Output Gaussian Process Toolkit Paper - API Documentation - Tutorials & Examples The Multi-Output Gaussian Process Toolkit is a Python toolkit f

GAMES 113 Nov 25, 2022
Official code base for the poster "On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation" published in NeurIPS 2021 Workshop (SVRHM)

Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio

Binxu 8 Aug 17, 2022