JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces

Overview

JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces

gallery roadmap metrics

JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in continuous spaces, with a particular emphasis on roadmap construction and evaluation. With JAXMAPP, You can:

  • Create MAPP problem instances with homogeneous/heterogeneous agents
  • Construct roadmaps and perform prioritized planning to solve MAPP
  • Develop and evaluate your own roadmap construction methods

Main contributors: Ryo Yonetani (@yonetaniryo), Keisuke Okumura (@Kei18)

Installation

The code has been tested on Ubuntu 16.04 and 18.04, as well as WSL2 (Ubuntu 20.04) on Windows 11. Planning can be performed only on the CPU, and the use of GPUs is also supported for training/evaluating machine-learning models. We also provide Dockerfile to replicate our setup.

venv

$ python -m venv .venv
$ source .venv/bin/activate
(.venv) $ make

Docker container

$ docker-compose build
$ docker-compose up -d dev
$ docker-compose exec dev bash

Docker container with CUDA enabled

$ docker-compose up -d dev-gpu
$ docker-compose exec dev-gpu bash

and update JAX modules in the container...

# pip install "jax[cuda]==0.2.25" -f https://storage.googleapis.com/jax-releases/jax_releases.html

Tutorials

Citation

@misc{jaxmapp_2022,
author = {Yonetani, Ryo and Okumura, Keisuke},
month = {2},
title = {JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces},
url = {https://github.com/omron-sinicx/jaxmapp},
year = {2022}
}


@inproceedings{okumura2022ctrm,
title={CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces},
author={Okumura, Keisuke and Yonetani, Ryo and Nishimura, Mai and Kanezaki, Asako},
booktitle={Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS)},
year={2022}
}
Owner
OMRON SINIC X
OMRON SINIC X
Detectorch - detectron for PyTorch

Detectorch - detectron for PyTorch (Disclaimer: this is work in progress and does not feature all the functionalities of detectron. Currently only inf

Ignacio Rocco 558 Dec 23, 2022
we propose EfficientDerain for high-efficiency single-image deraining

EfficientDerain we propose EfficientDerain for high-efficiency single-image deraining Requirements python 3.6 pytorch 1.6.0 opencv-python 4.4.0.44 sci

Qing Guo 126 Dec 07, 2022
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http

chenm 253 Dec 08, 2022
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io

495 Dec 28, 2022
Unet network with mean teacher for altrasound image segmentation

Unet network with mean teacher for altrasound image segmentation

5 Nov 21, 2022
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

Generative Deep Learning Teaching Machines to paint, write, compose and play The official code repository for examples in the O'Reilly book 'Generativ

David Foster 1.3k Dec 29, 2022
Code for technical report "An Improved Baseline for Sentence-level Relation Extraction".

RE_improved_baseline Code for technical report "An Improved Baseline for Sentence-level Relation Extraction". Requirements torch = 1.8.1 transformers

Wenxuan Zhou 74 Nov 29, 2022
Cross-platform CLI tool to generate your Github profile's stats and summary.

ghs Cross-platform CLI tool to generate your Github profile's stats and summary. Preview Hop on to examples for other usecases. Jump to: Installation

HackerRank 134 Dec 20, 2022
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene

Jiaxuan 568 Dec 29, 2022
Joint deep network for feature line detection and description

SOLD² - Self-supervised Occlusion-aware Line Description and Detection This repository contains the implementation of the paper: SOLD² : Self-supervis

Computer Vision and Geometry Lab 427 Dec 27, 2022
[CVPR 2022] CoTTA Code for our CVPR 2022 paper Continual Test-Time Domain Adaptation

CoTTA Code for our CVPR 2022 paper Continual Test-Time Domain Adaptation Prerequisite Please create and activate the following conda envrionment. To r

Qin Wang 87 Jan 08, 2023
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L

2.1k Jan 02, 2023
GenshinMapAutoMarkTools - Tools To add/delete/refresh resources mark in Genshin Impact Map

使用说明 适配 windows7以上 64位 原神1920x1080窗口(其他分辨率后续适配) 待更新渊下宫 English version is to be

Zero_Circle 209 Dec 28, 2022
Object Detection Projekt in GKI WS2021/22

tfObjectDetection Object Detection Projekt with tensorflow in GKI WS2021/22 Docker Container: docker run -it --name --gpus all -v path/to/project:p

Tim Eggers 1 Jul 18, 2022
This is my research project for the Irving Center for Cancer Dynamics/Azizi Lab, Columbia University.

bayesian_uncertainty This is my research project for the Irving Center for Cancer Dynamics/Azizi Lab, Columbia University. In this project I build a s

Max David Gupta 1 Feb 13, 2022
Art Project "Schrödinger's Game of Life"

Repo of the project "Team Creative Quantum AI: Schrödinger's Game of Life" Installation new conda env: conda create --name qcml python=3.8 conda activ

ℍ◮ℕℕ◭ℍ ℝ∈ᛔ∈ℝ 2 Sep 15, 2022
Code for "Learning to Segment Rigid Motions from Two Frames".

rigidmask Code for "Learning to Segment Rigid Motions from Two Frames". ** This is a partial release with inference and evaluation code.

Gengshan Yang 157 Nov 21, 2022
Self-Supervised Document-to-Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference

Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD

Microsoft 36 Nov 28, 2022
Streaming over lightweight data transformations

Description Data augmentation libarary for Deep Learning, which supports images, segmentation masks, labels and keypoints. Furthermore, SOLT is fast a

Research Unit of Medical Imaging, Physics and Technology 256 Jan 08, 2023
StyleGAN-Human: A Data-Centric Odyssey of Human Generation

StyleGAN-Human: A Data-Centric Odyssey of Human Generation Abstract: Unconditional human image generation is an important task in vision and graphics,

stylegan-human 762 Jan 08, 2023