Vector-based localization and map building for mobile robots using laser range finders in an indoor environment

Abstract

For a mobile robot to operate autonomously, it should fulfill three requirements: First, it should have knowledge about its operational environment. Second, it should be able to sense the outer environment. Third, it should be provided localization ability to estimate its current position. A mobile robot obtains environmental data using exteroceptive sensors, which is converted to the preferred type of information. The obtained information is compared to the knowledge database about the environment, i.e. map, and the current pose estimate is calculated by localization process. According to the availability of the initial pose, localization process is divided into two categories: local localization, also known as pose tracking, assumes that the initial robot pose is known. Hence, it focuses on the accuracy and speed of the localization process. The other approach, global localization concentrates on how to find the robot pose in a given map without initial guess. Hence, robustness is more important issue than algorithmic speed or accuracy. In addition, the environmental knowledge is not always available. A mobile robot in this situation should be able to build its own representation about the environment. To build an environmental map, however, the robot should know its current position. Approaches managing this problem are called SLAM (Simultaneous Localization And Mapping) or CML (Concurrent Mapping and Localization). In this dissertation, we deal with localization and SLAM problem for indoor mobile robots. Local localization algorithm based on proposed vector-matching makes it possible to estimate the robot`s pose more accurately and quickly than other approaches. On the other hand, traditional approaches for global localization problem does not guarantee the robustness of localization performance in an environment that is highly occupied with obstacles. We propose Vector Pattern Matching (VPM) scheme for global localization which helps effi...