Bundle adjustment revisited for SLAM with RGBD sensors

We present a method of using depth information provided by an RGB-D sensor, for visual simultaneous localization and mapping (SLAM), in order to improve its accuracy. We present a constraint bundle adjustment which allows to easily combine depth and visual data in cost function entirely expressed in pixel. The proposed approach is evaluated on a public benchmark dataset and compared to the state of art methods.