ORB-ODOM: Stereo and odometer sensor fusion for simultaneous localization and mapping
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Institute of Electrical and Electronics Engineers (IEEE)
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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.
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Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017, v. 2017-December, p. 1-5.
