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

• Autor(a) principal: Caldato, Brenno A. C. [UNESP]
• Data de Publicação: 2017
• Outros Autores: Achilles Filho, Ricardo [UNESP], Castanho, Jose Eduardo C. [UNESP], Todt, E., Tonidandel, F.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/163959

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.