An integrated mobile robot path (Re)planner and localizer for personal robots

Personal robotics applications require autonomous mobile robot navigation methods that are safe, robust, and inexpensive. Most of the previous techniques proposed do not meet these competing goals. In this paper, we describe a method for navigation in a known indoor environment, such as a home or office, that requires only inexpensive range sensors. Our framework includes a high-level planner which integrates and coordinates path planning and localization modules with the aid of a module for computing regions which are expected, with high probability, to contain the robot at any given time. The localization method is based on simple geometric properties of the environment which are computed during a preprocessing stage. The roadmap-based path planner enables one to select routes, and sub-goals along those routes, that will facilitate localization and other optimization criteria. In addition, our framework enables one to quickly plan new routes, dynamically, based on the current position as computed by in termediate localization operations. We present simulation and hardware experimental results that illustrate the practicality and potential of our approach.