The SLAM module is part of the sensor dynamics component. When the rc_visard moves through the world, its pose estimate slowly accumulates errors over time. The SLAM module can correct these pose errors by recognizing previously visited places.
The acronym SLAM stands for Simultaneous Localization and Mapping. The SLAM module creates a map consisting of the image features used in visual odometry. The map is later used to correct accumulated pose errors. This is most apparent in applications where the robot returns to a previously visited place after covering a large distance (this is called a “loop closure”). In this case, the robot can redetect image features that are already stored in its map and can use this information to correct the pose estimate. When closing a loop, not only the current pose, but also the past pose estimates (the trajectory of the rc_visard), are corrected. Continuous trajectory correction leads to a more accurate map. On the other hand, the accuracy of the full trajectory is important when it is used to build an integrated world model, e.g., by projecting the obtained 3D point clouds obtained (see Computing depth images and point clouds) into a common coordinate frame. The full trajectory can be requested from the SLAM module for this purpose.
The SLAM module will be optionally available for the rc_visard and will run on board the sensor. If a SLAM license is stored on the rc_visard, then the SLAM module is shown as Available on the Web GUI’s Overview tab, and it can be switched on and off on the same page.