Litcius/Paper detail

iDROP: Robust Localization for Indoor Navigation of Drones With Optimized Beacon Placement

Alireza Famili, Angelos Stavrou, Haining Wang, Jung‐Min Park

2023IEEE Internet of Things Journal37 citationsDOI

Abstract

Drones in many applications need the ability to fly fully or partially autonomously to accomplish their mission. To allow these fully/partially autonomous flights, first, the drone needs to be able to locate itself constantly. Then, the navigation command signal would be generated and passed on to the controller unit of the drone. In this article, we propose a localization scheme for drones called robust localization for indoor navigation of drones with optimized beacon placement (iDROP) that is specifically devised for GPS-denied environments (e.g., indoor spaces). Instead of GPS signals, iDROP relies on speaker-generated ultrasonic acoustic signals to enable a drone to estimate its location. In general, localization error is caused by two factors: the ranging error and the error induced by relative geometry between the transmitters and the receiver. iDROP mitigates these two types of errors and provides a high-precision 3-D localization scheme for drones. iDROP employs a waveform that is robust against multipath fading. Moreover, placing beacons in optimal locations reduces the localization error induced by the relative geometry between the transmitters and the receiver.

Topics & Concepts

DroneBeaconComputer scienceMultipath propagationGlobal Positioning SystemReal-time computingGPS signalsTransmitterAssisted GPSTelecommunicationsGeneticsBiologyChannel (broadcasting)Indoor and Outdoor Localization TechnologiesUnderwater Vehicles and Communication SystemsRobotics and Sensor-Based Localization