Monocular Visual Odometry Using Fisheye Lens Cameras

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

André Aguiar (Author) Other; Filipe Neves Santos (Author) FEUP; Luís Santos (Author) Other; Armando Jorge Sousa (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 319-330

19th EPIA Conference on Artificial Intelligence, EPIA 2019

3 September 2019 through 6 September 2019

Indexing

Scopus - 5 Citations

Other information

Authenticus ID: P-00R-03B

DOI: 10.1007/978-3-030-30244-3_27

Abstract (EN): Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System. In this context, a reliable localization system requires an accurate and redundant information to Global Navigation Satellite System and wheel odometry based system. To pursue this goal and have a reliable localization system in our robotic platform we aim to extract the better performance as possible from a monocular Visual Odometry method. To do so, we present a benchmark of Libviso2 using both perspective and fisheye lens cameras, studying the behavior of the method using both topologies in terms of motion performance in an outdoor environment. Also we analyze the quality of feature extraction of the method using the two camera systems studying the impact of the field of view and omnidirectional image rectification in VO. We propose a general methodology to incorporate a fisheye lens camera system into a VO method. Finally, we briefly describe the robot setup that was used to generate the results that will be presented. © 2019, Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12