Multi-robot SLAM system

[IEEE T-RO 2023] A modularized multi-robot SLAM system with elevation mapping and a costmap converter for easy navigation. Different odometry and loop closure algorithms can be easily integrated into the system.

M3DGR: A Multi-sensor, Multi-scenario and Massive-baseline SLAM Dataset for Ground Robots(IROS2025)

SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation

A Multi-sensor SLAM Dataset Focusing on Corner Cases for Ground Robots (ROBIO2023)

Extension and update of M2DGR: a novel Multi-modal and Multi-scenario SLAM Dataset for Ground Robots (ICRA2022 & ICRA2024)

A large-scale multi-robot dataset for multi-robot SLAM

Ready to test your SLAM system in challenging datasets from extreme environments? Try this out! The dataset is provided by the Team CoSTAR that has been intensively testing multi-robot systems in real world environments such as caves, tunnels, abandoned factories and industrial plants for the DARPA Subterranean Challenge.

[RA-L] S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM

Decentralized Multi-Robot Graph Simultaneous Localization and Mapping

Multi-robot control simulation environmrnt build on top on Mobile Robotics Simulation Toolbox, implemented 1)some algorithm for formation control 2)mapping, localization and SLAM based on Kalman filter..

多平台搭建SLAM系统，包括(轮式底盘、四足机器人、无人机、无人船、轮腿式机器人等)，复现3D-SLAM开源算法，如：LEGO-LOAM、LIO-SAM、LVI-SAM、FAST-LIO、R2LIVE、R3LIVE等~

Recent multi-robot projects and papers: Including SLAM, place recognition, Large Language Models navigation. (continually updated)

A ROS package that implements a multi-robot SLAM system using the condensed graphs approach

Video recording app with sub-millisecond synchronization accuracy for multiple Android smartphones, useful for creating affordable and easy-to-setup multi-view camera systems for robotics, SLAM, 3D-reconstruction, panorama stitching

Repository for project VIR-SLAM, Visual, Inertial, and Ranging SLAM for Single and Multi-Robot Systems

extension and update of M2DGR: a Multi-modal and Multi-scenario SLAM Dataset for Ground Robots (ICRA2022 & ICRA2024)

An example about using anchor node for multi-robot and -session slam

[IROS 2024]: Multi-robot active graph exploration with reduced pose-SLAM uncertainty via submodular optimization.

A simple Multi-Robot SLAM solution that communicates efficiently. The result of my M.Sc. work.

Code for RA-L paper "Multi-Robot Object SLAM using Distributed Variational Inference"

This repo is an implementation version of Liorf(LIO-SAM modification) and DiSCO-SLAM in order to run a multi-Robot SLAM with better LIO-SAM performance

Based off of multi_map_merge package: http://wiki.ros.org/multirobot_map_merge. Modified for multi-robot coordinated SLAM.

No description available

Collection of multi-robot SLAM algorithms for ROS

README.md AGV-Fleet-Management-System Project Description: The current industrial revolution mainly focuses on automation, artificial intelligence, and interconnectivity to optimize and manage the production processes and supply chain. As a result of it, AGVs are used in a range of industries to handle and transport items from one place to another. Currently, most of the AGVs in operations are portable and follow marking lines or magnets on the floor for navigation from one location to another. Since this type of AGV is restricted to travels only on dedicated paths, is less flexible, and gets stopped when comes in contact with obstacles, our project focuses on improving the flexibility of AGVs by decision making and navigating to the desired goal location with im-mobile and mobile obstacle avoidance. Implementation of our objective is divided into three main parts - mapping, localization, and navigation of an AGVs in the environment. ROS framework is used to code, coppeliasim and Rviz tool is used to visualize the simulation process. Methodology : Mapping - Simultaneous Localisation And Mapping Navigation Stack - Move base Global planner - NavfnROS ( Based on dijkstra algorithm ) Local planner - Dynamic Window Approach Localisation - Adaptive Monte Carlo Localisation Installation Tested with ROS 1 neotic under ubuntu 20.04 Works 1) Warehouse Environment created in Coppeliasim and mapping is done with SLAM alogirthm image 2) Localisation of Robot using AMCL image 3) global and local planner visualisation in Rviz image Fig:-3.1 Setting up of navigation goal image Fig:-3.2 global plan visualisation image Fig:-3.3 Local plan visualisation 4) Updating Obstacles in the map visualisation image 5) working of multi-bot navigation image

Multi-Robot Graph SLAM Simulation

The goal of this project is to detect separators (transforms) between frames of the same places encountered by different robots for multi-robot SLAM

2D Multi Robot Visual Graph SLAM. This approach is specially addressed to underwater or marine surface vehicles with cameras pointing downwards to the seabed. Althought not tested, It could be also applied to terrestrial vehicles with a camera facing the ground. Non suitable for vehicles moving with 6 DoF.

heteregeneous multi-robot stereo-visual and inertial dataset for collaborative SLAM