A Version of Libviso2 for Central Dioptric Omnidirectional Cameras with a Laser-Based Scale Calculation

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Aguiar, A (Author) Other; Filipe Neves Santos (Author) FEUP; Santos, L (Author) Other; Armando Jorge Sousa (Author) FEUP

Conference proceedings International

Title: FOURTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, ROBOT 2019, VOL 1

Pages: 127-138

4th Iberian Robotics Conference (Robot) - Advances in Robotics

Porto, PORTUGAL, NOV 20-22, 2019

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00R-CG3

DOI: 10.1007/978-3-030-35990-4_11

Abstract (EN): Monocular Visual Odometry techniques represent a challenging and appealing research area in robotics navigation field. The use of a single camera to track robot motion is a hardware-cheap solution. In this context, there are few Visual Odometry methods on the literature that estimate robot pose accurately using a single camera without any other source of information. The use of omnidirectional cameras in this field is still not consensual. Many works show that for outdoor environments the use of them does represent an improvement compared with the use of conventional perspective cameras. Besides that, in this work we propose an open-source monocular omnidirectional version of the state-of-the-art method Libviso2 that outperforms the original one even in outdoor scenes. This approach is suitable for central dioptric omnidirectional cameras and takes advantage of their wider field of view to calculate the robot motion with a really positive performance on the context of monocular Visual Odometry. We also propose a novel approach to calculate the scale factor that uses matches between laser measures and 3-D triangulated feature points to do so. The novelty of this work consists in the association of the laser ranges with the features on the omnidirectional image. Results were generate using three open-source datasets built in-house showing that our unified system largely outperforms the original monocular version of Libviso2.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12