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

Unofficial Pytorch Implementation of WaveGrad2

Birthday-problem - The birthday problem asks for the probability that, in a set of n randomly chosen people, at least two will share a birthday

General Vision Benchmark, a project from OpenGVLab

[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

Learning Dense Representations of Phrases at Scale (Lee et al., 2020)

OpenDILab Multi-Agent Environment

A Python Package for Portfolio Optimization using the Critical Line Algorithm

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces"

The spiritual successor to knockknock for PyTorch Lightning, get notified when your training ends

This is the pytorch re-implementation of the IterNorm

ZSL-KG is a general-purpose zero-shot learning framework with a novel transformer graph convolutional network (TrGCN) to learn class representation from common sense knowledge graphs.

Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper

A series of Python scripts to access measurements from Fluke 28X meters. Fluke IR Remote Interface required.

Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021)

FinRL­-Meta: A Universe for Data­-Driven Financial Reinforcement Learning. 🔥

a practicable framework used in Deep Learning. So far UDL only provide DCFNet implementation for the ICCV paper (Dynamic Cross Feature Fusion for Remote Sensing Pansharpening)

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