*Result*: Global positioning system denied navigation of visual simultaneous localisation and mapping generated maps
*Further Information*
*Mulubika, C. 2025. Global Positioning System Denied Navigation of Visual Simultaneous Localisation and Mapping Generated Maps. Unpublished doctoral dissertation. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/d2c63575-e099-4ffa-a42e-5c0e1bf24854 ; Thesis (PhD)--Stellenbosch University, 2025. ; ENGLISH ABSTRACT: This dissertation is centred on how a mobile robot platform can make use of visual simultaneous localization and mapping (vSLAM) to get back to a required position in case of camera malfunction or loss of visual capabilities during its mission. It assumes that the environment in which it is operating is both global positioning system (GPS) denied and static. With loss of visual capabilities or camera malfunction in vSLAM, the robot has limited sources of sensor data. Here it is assumed that only the inertial measurement unit (IMU) sensors remain when visual input is not present. Hence data previously generated during vSLAM activities when visual input was available provide an attractive solution to get anywhere in the previously traversed path. To select data needed for blind navigation, the path is treated as a signal that needs to be reconstructed were ego-motion from IMU sensors and image data are the primary source of information. Image data guides the ego-motion along safe passages while ego-motion parameters are periodically sampled during vSLAM map generation. From ego-motion, twist velocities, distance covered, the sampling period and yaw angles are used as path landmarks to describe the path. The yaw angles are further used in segregating path segments into straight and curved segments by assigning them two different sampling periods, one half of the other, with the straight getting the higher value. The path landmarks are stored in a YAML file and uniquely labelled from the start to the point of camera malfunction or loss of visual capabilities. The sampling, storage, and use of the path landmarks use the robot operating system (ROS) software ...*