The Interconnectivity Between SLAM and Autonomous Exploration : Investigation Through Integration

Abstract: Two crucial functionalities of a fully autonomous robotic agent are localization and navigation. The problem of enabling an agent to localize itself in an unknown environment is an extensive and widely studied topic. One of the main areas of this topic focuses on Simultaneous Localization and Mapping (SLAM). Many advancements in this field have been made over the years resulting in robust and accurate localization systems. Navigation progress has also improved substantially throughout the years resulting in efficient path planning algorithms and effective exploration strategies. Although an abundance of research exists on these two topics, less so exists about the combination of the two and their effect on each other. Therefore, the aim of this thesis was to integrate two state-of-the-art components from each respective area of research into a functioning system. This was done with the aim of studying the interconnectivity between these components while also documenting the integration process and identifying important considerations for similar future endeavours. Evaluations of the system showed that it performed with surprisingly good accuracy although it was severely lacking in robustness. Integration efforts showed good promise; however, it is clear that the two fields are heavily linked and need to be considered in a mutual context when it comes to a complete integrated system.