Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework

Mobile robots need to be fully autonomous in order to perform their tasks inside their environment. To do that, robots need to have an understanding of their environment, so that they can successfully localize and navigate themselves within it. The understanding of the robots' environment is created by solving the SLAM (Simultaneous Localization...

Local Accuracy in Global Uncertainty: The Design of a Particle Filter Based Hybrid Metric-Topological Mapping and Localization Framework

Mobile robots need to interact with their environment to perform their tasks. To be successful they often need to know what their surrounding looks like, and where they are located in that surrounding. The act of simultaneously estimating both the state of the robot and the state of the environment is called Simultaneous Localization And Mapping...