Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment

Last update: Nov 22, 2022

Overview

Voronoi Multi_Robot Collaborate Exploration

Introduction

In the unknown environment, the cooperative exploration of multiple robots is completed by Voronoi partition and deep reinforcement learning. The decision-making level assigns different target positions to each mobile robot through Voronoi partition and point selection formula to minimize repeated exploration; The path planning layer uses the method based on deep reinforcement learning to make each mobile robot reach the corresponding target position without collision.

Enviroment

parameter	description
system	Ubuntu18.04 ; ROS(Melodic); Phython 2.7
simulator	Gazebo
display	Rviz
simulation car	Turtlebot3(Waffle)
senor	LiDAR
laser range	0.1 - 3.5 m
angle range	-90 - 90
laser numer	24

Run

dependency package

sudo apt-get install ros-melodic-joy ros-melodic-teleop-twist-joy ros-melodic-teleop-twist-keyboard ros-melodic-laser-proc ros-melodic-rgbd-launch ros-melodic-depthimage-to-laserscan ros-melodic-rosserial-arduino ros-melodic-rosserial-python ros-melodic-rosserial-server ros-melodic-rosserial-client ros-melodic-rosserial-msgs ros-melodic-amcl ros-melodic-map-server ros-melodic-move-base ros-melodic-urdf ros-melodic-xacro ros-melodic-compressed-image-transport ros-melodic-rqt-image-view ros-melodic-gmapping ros-melodic-navigation ros-melodic-interactive-markers ros-melodic-multirobot-map-merge

Add

pyyaml、rospkg、pytorch、torchvision、tensorflow 、tensorboard、mpi4py、joblib、gym、pathlib、wandb、Image、setproctitle、imageio

compile & run

> catkin_make 
> source devel/setup.bash
> roslaunch multi_turtlebot3_expore three_turtlebot3_gmapping.launch
> python ddpg_test.py

test

Move & mapping

Comparison of construction effects

Run in other environments

Avoid obstacle

Reference

hanlinniu/turtlebot3_ddpg_collision_avoidance：https://github.com/hanlinniu/turtlebot3_ddpg_collision_avoidance

Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment

Related tags

Overview

Voronoi Multi_Robot Collaborate Exploration

Introduction

Enviroment

Run

dependency package

compile & run

test

Move & mapping

Run in other environments

Reference

Owner

PeaceWord

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Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment

Related tags

Overview

Voronoi Multi_Robot Collaborate Exploration

Introduction

Enviroment

Run

dependency package

compile & run

test

Move & mapping

Run in other environments

Reference

Owner

PeaceWord

Source code for paper "ATP: AMRize Than Parse! Enhancing AMR Parsing with PseudoAMRs" @NAACL-2022

Resources for our AAAI 2022 paper: "LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification".

Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs

Official repository for the paper "Self-Supervised Models are Continual Learners" (CVPR 2022)

Source code for our paper "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations"

Hierarchical Attentive Recurrent Tracking

Code for "On Memorization in Probabilistic Deep Generative Models"

A code repository associated with the paper A Benchmark for Rough Sketch Cleanup by Chuan Yan, David Vanderhaeghe, and Yotam Gingold from SIGGRAPH Asia 2020.

PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021)

A toolkit for making real world machine learning and data analysis applications in C++

Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)

“英特尔创新大师杯”深度学习挑战赛 赛道3：CCKS2021中文NLP地址相关性任务

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Analysis of rationale selection in neural rationale models

This is the official PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning".

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这是一个facenet-pytorch的库，可以用于训练自己的人脸识别模型。

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