Autonomous Systems: Autonomous Systems: Indoor Drone Navigation

TL;DR

This paper presents a novel approach to indoor drone navigation using ROS frameworks, demonstrating autonomous movement in simulated environments without GPS, which advances UAV autonomy in complex indoor settings.

Contribution

The work adapts ROS navigation tools for UAVs, enabling autonomous indoor navigation in simulation, a task previously unachieved with these systems.

Findings

Successful simulation of autonomous indoor drone navigation

Integration of SLAM toolbox with Nav2 for UAVs

Demonstrated potential for autonomous indoor UAV operations

Abstract

Drones are a promising technology for autonomous data collection and indoor sensing. In situations when human-controlled UAVs may not be practical or dependable, such as in uncharted or dangerous locations, the usage of autonomous UAVs offers flexibility, cost savings, and reduced risk. The system creates a simulated quadcopter capable of autonomously travelling in an indoor environment using the gazebo simulation tool and the ros navigation system framework known as Navigaation2. While Nav2 has successfully shown the functioning of autonomous navigation in terrestrial robots and vehicles, the same hasn't been accomplished with unmanned aerial vehicles and still has to be done. The goal is to use the slam toolbox for ROS and the Nav2 navigation system framework to construct a simulated drone that can move autonomously in an indoor (gps-less) environment.