QDR: A Quadrotor Dead Reckoning Framework

Artur Shurin,Itzik Klein

doi:10.1109/access.2020.3037468

Abstract

Quadrotors are used for variety of applications both outdoors and indoors. Among them are - deliveries, surveillance, transportation, mapping and more. To accomplish its tasks an accurate navigation solution is required. To that end, most quadrotors apply fusion between an inertial navigation system and other external sensors, such as global navigation satellite systems (outdoors) or vision (indoors/outdoors). Due to environmental or sensor constraints, in some portion of the trajectory, the navigation solution relies only on the inertial navigation system solution. Consequently, the navigation solution drifts in time due to errors and noise in the inertial sensors measurements. Motivated from the pedestrian dead reckoning approach, we propose the quadrotor dead-reckoning framework to mitigate the navigation solution drift in situations of pure inertial navigation. There, instead of a straight line trajectory, the quadrotor is flown with a periodic motion to enable peak to peak distance estimation. Simulation and experiments results show that the proposed approach greatly improves the accuracy of the navigation solution.

Highlights

Q Uadrotors are used for a growing variety of applications both for outdoor and indoor environments
global navigation satellite systems (GNSS) is not available for indoor environments, which leads to different types of navigation solutions such as simultaneously localization and mapping (SLAM) [8], [9],visual positioning [10], [11], [12] and inertial navigation system (INS) fusion with other sensors such as Wi-Fi [13], [14]
The body frame acceleration and angular velocity vectors required for QDR periodic motion are defined using a simplified kinematic model

Summary

Introduction

Q Uadrotors are used for a growing variety of applications both for outdoor and indoor environments. Among them are - industrial use, military applications, construction field, surveillance, transportation, mapping, emergency response and law enforcement in public areas. GNSS is not available for indoor environments, which leads to different types of navigation solutions such as simultaneously localization and mapping (SLAM) [8], [9] ,visual positioning [10], [11], [12] and inertial navigation system (INS) fusion with other sensors such as Wi-Fi [13], [14]. In some situations visual conditions are not sufficient, disabling SLAM applications and usually resulting in pure inertial navigation. In outdoors GNSS is not always available like in urban canyons and other environments and again the quadrotors navigation solution will depend only on the INS solution and will drift in time.

Methods

Results

Conclusion