Conference

Vision-Based Unmanned Aerial Vehicle Pose Correction Using a Digital Model

2026 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Mariana Campos; Nuno Pessanha Santos; Alexandre Bernardino2026IEEE

Key information

Authors:

Mariana Campos; Nuno Pessanha Santos (Nuno Alexandre Antunes Martins Pessanha Santos); Alexandre Bernardino (Alexandre José Malheiro Bernardino)

Published in

May 20, 2026

Abstract

Unmanned Aerial Vehicles (UAVs) are extensively used in remote sensing applications such as wildfire monitoring, where precise georeferencing is critical. However, onboard navigation sensors, including Global Navigation Satellite System (GNSS) receivers and Inertial Measurement Units (IMUs), are prone to errors that can affect downstream processing. This paper introduces a UAV pose correction framework based on synthetic view generation and image-based matching. UAV telemetry, smoothed with a constant-velocity Kalman filter, is used to generate synthetic views, which are then matched to real UAV images using Detector-Free Local Feature Matching with Transformers (LoFTR). The correspondences obtained are ray-cast into a digital surface model to recover 3D points, which are subsequently employed for camera pose refinement via Perspective-n-Point estimation using the Sequential Quadratic Programming PnP (SQPnP) algorithm. The approach is tested on an aerial dataset collected over a forested area at an average altitude of 1678 m. Experimental results reveal horizontal and vertical RMSEs of 3.32 m and 2.21 m, respectively, with orientation errors below 0.2°. Further refinement using an Improved Innovation Adaptive Kalman Filter (IAKF) reduces the horizontal and vertical RMSEs to 2.24 m and 1.01 m, respectively. These findings demonstrate the effectiveness of the proposed method for robust UAV pose correction.

Publication details

Publication version

AM - Accepted manuscript

Publisher

IEEE

Link to the publisher's version

https://ieeexplore.ieee.org/abstract/document/11523313

Title of the publication container

2026 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Location of the conference

Barcelos, Portugal

Conference date start

April 22, 2026

Conference date end

April 23, 2026

Fields of Science and Technology (FOS)

electrical-engineering-electronic-engineering-information-engineering - Electrical engineering, electronic engineering, information engineering

Keywords

  • Autonomous aerial vehicles
  • Modeling
  • Filtering
  • Telemetry
  • Cameras
  • Kalman filters
  • Digital Model
  • Pose Correction
  • Camera pose estimation
  • Pose estimation
  • Temporal Filtering

Publication language (ISO code)

eng - English

Rights type:

Only metadata available

Financing entity

Fundação para a Ciência e a Tecnologia

Title of the project, award or grant: LA/P/0083/2020, UIDP/50009/2020, UIDB/50009/2020

Identifier for the funding entity: https://doi.org/10.13039/501100001871

Type of identifier of the funding entity: Crossref Funder