ORB-ODOM: Stereo and Odometer Sensor Fusion for Simultaneous Localization and Mapping

Autor(es)

Caldato, Brenno A. C. ; Achilles Filho, Ricardo ; Castanho, Jose Eduardo C. ; Todt, E ; Tonidandel, F

• Tipo de documento: Artigo Científico
• Fonte: 2017 LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS) AND 2017 BRAZILIAN SYMPOSIUM ON ROBOTICS (SBR); v. N/A, p. 5-pg., 2017-01-01.

Resumo

ORB-SLAM2 is one of the better-known open source SLAM implementations available. However, the dependence of visual features causes it to fail in featureless environments. With the present work, we propose a new technique to improve visual odometry results given by ORB-SLAM2 using a tightly Sensor Fusion approach to integrate camera and odometer data. In this work, we use odometer readings to improve the tracking results by adding graph constraints between frames and introduce a new method for preventing the tracking loss. We test our method using three different datasets, and show an improvement in the estimated trajectory, allowing a continuous tracking without losses. (AU)

• Processo FAPESP: 10/50650-3 - Modernização dos laboratórios dos cursos de pós-graduação em engenharias da UNESP de Bauru
• Beneficiário: Heraldo Luiz Giacheti
• Modalidade de apoio: Auxílio à Pesquisa - Regular