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Glossary

Dataset	Camera, IMU and other sensor data collected, for example, using the SLAMcore Dataset Recorder tool. Each dataset can be used as an input to create a session.
Gyroscope	Measures the orientation and angular velocity of the camera.
IMU	An inertial measurement unit (IMU) measures the device’s specific force, angular rate and orientation.
Localisation Mode	Sometimes also referred to as “multisession” or “multisession localisation”. In this mode, a map that was previously created in SLAM mode is loaded into the session, and the SLAM system localises against this existing map. New landmarks are discovered and used for tracking in localisation mode but these will not be added to the existing map or saved at the end of the run. See the Localisation Mode tutorial for more.
Loop Closure	The assertion that the system has returned to a previously visited location and updating pose estimation beliefs accordingly.
Point Cloud	A point-cloud in this context is defined as a persistent map of individual points that are plotted in three dimensions.
ROS	The Robot Operating System is a flexible framework for writing robot software. See https://www.ros.org/
Session	Instance during which a live camera feed or a dataset is processed to output pose and mapping data.
Session File	SLAMcore file with a .session file extension containing the mapping data created after processing a live camera feed or dataset.
SLAM	Simultaneous localization and mapping: constructing or updating a map of an unknown environment while simultaneously keeping track of an agent or robot’s location within the environment.
SLAM Mode	In SLAM mode, the system tracks and stores the location of natural features to create a live point-cloud which is used to calculate the real-time position of the robot. In this mode it is possible to detect locations that have been visited before, triggering a loop closure and correcting for any drift that may have accumulated. See the Single Session SLAM Positioning Mode tutorial for more.
Visual-Inertial Tracking System	A system that uses visual features from camera(s) and inertial data from an IMU to determine the position of the device.
Visual Odometry	The process of determining the position and orientation of the camera by analysing the camera images.
Visual-Inertial Odometry Mode	In this mode, the system tracks the location of natural features to create a live point-cloud and calculate the the real-time position of the robot. However, it does not store any history of these features or the historic position estimates of the robot. The position estimate is smooth but subject to drift over time. See the Visual-Inertial Odometry Positioning tutorial for more.