| Accurate sensing of vehicle location and attitude is a fundamental requirement in many mobile-robot applications, but is a very challenging problem in the cluttered and unstructured environment of the real world.{09}Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines of sight or do not provide absolute, drift-free measurements. Examples include overhead vision systems, where an unobstructed view must be maintained between robot and camera, and inertial systems, where the measurements drift over time.; The research presented in this dissertation provides a new location- and attitude-sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building or warehouse. The system is not limited by line-of-sight restrictions and produces drift-free measurements throughout a three-dimensional operating volume that can span a large building. Accuracy of several centimeters and a few degrees is delivered at 10 Hz, and any number of the small sensor units can be in operation, all providing estimates in a common reference frame.; This positioning system is based on extremely-low-frequency magnetic fields, which have excellent characteristics for penetrating line-of-sight obstructions. Beacons located throughout the workspace create the low-level fields. A sensor unit on the mobile robot samples the local magnetic field and processes the measurements to determine its location and attitude.; This research overcomes limitations in existing magnetic-based systems. The design of the signal structure, based on pseudorandom codes, enables the use of multiple, distributed{09}L-beacons and greatly expands coverage volume. The development of real-time identification and correction methods mitigates the impact of distortions caused by materials in the environment. A novel solution algorithm combats both challenges, providing increased coverage volume and reduced sensitivity to materials.; This dissertation examines the concept for the system, the challenges encountered during its development, the research solutions that enable the system, the design of a prototype, and results from experimental demonstrations. The positioning system developed through this research provides an effective solution not only for mobile robots navigating cluttered environments, but has application in other areas such as object tracking, augmented reality, and construction. |
