ICUAS'22 Paper Abstract

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Paper WeA4.4

Bednar, Jan (Czech Technical University in Prague VAT68407700), Petrlik, Matej (Czech Technical University FEE), Kelen, Vivaldini (UFSCar), Saska, Martin (Czech Technical University in Prague FEE)

Deployment of Reliable Visual Inertial Odometry Approaches for Unmanned Aerial Vehicles in Real-World Environment

Scheduled for presentation during the Regular Session "UAS Perception" (WeA4), Wednesday, June 22, 2022, 11:30−11:50, Divona-2

2022 International Conference on Unmanned Aircraft Systems (ICUAS), June 21-24, 2022, Dubrovnik, Croatia

This information is tentative and subject to change. Compiled on April 19, 2024

Keywords Sensor Fusion, Integration, Reliability of UAS

Abstract

Integration of Visual Inertial Odometry (VIO) methods into a modular control system designed for deployment of Unmanned Aerial Vehicles (UAVs) and teams of cooperating UAVs in real-world conditions is presented in this paper. Reliability analysis and fair performance comparison of several methods integrated into a control pipeline for achieving full autonomy in real conditions is provided. Although most VIO algorithms achieve excellent localization precision and negligible drift on artificially created datasets, the aspects of reliability in non-ideal situations, robustness to degraded sensor data, and the effects of external disturbances and feedback control coupling are not well studied. These imperfections, which are inherently present in cases of real-world deployment of UAVs, negatively affect the ability of the most used VIO approaches to output a sensible pose estimation. We identify the conditions that are critical for a reliable flight under VIO localization and propose workarounds and compensations for situations in which such conditions cannot be achieved. The performance of the UAV system with integrated VIO methods is quantitatively analyzed w.r.t. RTK ground truth and the ability to provide reliable pose estimation for the feedback control is demonstrated onboard a UAV that is tracking dynamic trajectories under challenging illumination.

 

 

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