EFFICIENT MULTI-ROBOT SLAM IN A LABYRINTH ENVIRONMENT: A DECENTRALIZED APPROACH USING ALGEBRAIC CONNECTIVITY AUGMENTATION

Abstract

This project focuses on implementing a multi-robot Simultaneous Localization and Mapping (SLAM) framework using multiple Turtlebots in a labyrinth environment. The goal is to demonstrate that multiple robots working together can map a complex environment more e!ciently than a single robot. Using the CSLAM framework, a decentralized approach, the project addresses key challenges like communication e!ciency, loop closure detection, and pose graph optimization. Preliminary work includes learning ROS, connecting LIDAR sensors, and generating point clouds.