Sensor based localization for multiple mobile robots using virtual links

Mobile robots are used for a wide range of purposes such as mapping an environment and transporting material goods. Regardless of the specific application, the navigation of the mobile robot is usually divided into three separate parts: localization, path planning and path execution. Localization is the process of determining the location of the robot with respect to a reference coordinate system. There are many different approaches to localizing a mobile robot which employ a wide variety of sensors. The objective of my research is to develop a method for the localization of multiple mobile robots equipped with inexpensive range sensors in an indoor environment. Each mobile robot will be equipped with a rotating infrared sensor and a rotating CMOS camera. The multiple mobile robot system will be treated as a linked robot for localization. The proposed localization method is verified via both simulation and experiment. Through the use of the virtual link length and relative heading information, a system of mobile robots can be effectively localized using detected environmental features

A framework for roadmap-based navigation and sector-based localization of mobile robots

Personal robotics applications require autonomous mobile robot navigation methods that are safe, robust, and inexpensive. Two requirements for autonomous use of robots for such applications are an automatic motion planner to select paths and a robust way of ensuring that the robot can follow the selected path given the unavoidable odometer and control errors that must be dealt with for any inexpensive robot. Additional difficulties are faced when there is more than one robot involved. In this dissertation, we describe a new roadmapbased method for mobile robot navigation. It is suitable for partially known indoor environments and requires only inexpensive range sensors. The navigator selects paths from the roadmap and designates localization points on those paths. In particular, the navigator selects feasible paths that are sensitive to the needs of the application (e.g., no sharp turns) and of the localization algorithm (e.g., within sensing range of two features). We present a new sectorbased localizer that is robust in the presence of sensor limitations and unknown obstacles while still maintaining computational efficiency. We extend our approach to teams of robots focusing on quickly sensing ranges from all robots while avoiding sensor crosstalk, and reducing the pose uncertainties of all robots while using a minimal number of sensing rounds. We present experimental results for mobile robots and describe a webbased route planner for the Texas A&M campus that utilizes our navigator