Self exploration and mapping for indoor robotic applications

This thesis presents an autonomous self-exploration and mapping system for use with indoor robotic-based applications. For most indoor robotic applications, prior information of the environment by the construction of a map is needed before a mobile robotic system can be deployed. An imperative need for a robotic system that is capable of safely navigating and mapping an unknown environment autonomously, with little to no need for human interaction, is apparent. Truly autonomous navigation requires self-exploration in an unknown environment and detection of edge-case obstacles such as complex or negative obstacles. A 3D LIDAR and depth camera was selected and the integration of a developed exploration and obstacle detection algorithm with open-source ROS-based software was used to achieve full autonomy. The developed system was tested in multiple indoor environments and was successful in navigating and mapping unknown environments.Mechanical Engineerin