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ORB-ODOM: Stereo and Odometer Sensor Fusion for Simultaneous Localization and Mapping
Fecha
2017-01-01Registro en:
2017 Latin American Robotics Symposium (lars) And 2017 Brazilian Symposium On Robotics (sbr). New York: Ieee, 5 p., 2017.
WOS:000426897500033
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
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.