Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion

Warren, Michael, Corke, Peter, Pizarro, Oscar, Williams, Stefan, & Upcroft, Ben (2012) Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion. In Australasian Conference on Robotics and Automation, 3-5 December 2012, Wellington, New Zealand.

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Abstract

In most visual mapping applications suited to Autonomous Underwater Vehicles (AUVs), stereo visual odometry (VO) is rarely utilised as a pose estimator as imagery is typically of very low framerate due to energy conservation and data storage requirements. This adversely affects the robustness of a vision-based pose estimator and its ability to generate a smooth trajectory. This paper presents a novel VO pipeline for low-overlap imagery from an AUV that utilises constrained motion and integrates magnetometer data in a bi-objective bundle adjustment stage to achieve low-drift pose estimates over large trajectories.

We analyse the performance of a standard stereo VO algorithm and compare the results to the modified vo algorithm. Results are demonstrated in a virtual environment in addition to low-overlap imagery gathered from an AUV. The modified VO algorithm shows significantly improved pose accuracy and performance over trajectories of more than 300m. In addition, dense 3D meshes generated from the visual odometry pipeline are presented as a qualitative output of the solution.

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ID Code: 55403
Item Type: Conference Paper
Refereed: Yes
Keywords: Visual Odometry, Bundle Adjustment, Autonomous Underwater Vehicle, Field Robotics
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Please consult the authors.
Deposited On: 10 Dec 2012 06:22
Last Modified: 21 Feb 2013 05:27

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