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Magnetic Field Aided Indoor Navigation, William F. Storms
Magnetic Field Aided Indoor Navigation, William F. Storms
Theses and Dissertations
This research effort examines inertial navigation system aiding using magnetic field intensity data and a Kalman filter in an indoor environment. Many current aiding methods do not work well in an indoor environment, like aiding using the Global Positioning System. The method presented in this research uses magnetic field intensity data from a three-axis magnetometer in order to estimate position using a maximum – likelihood approach. The position measurements are then combined with a motion model using a Kalman filter. The magnetic field navigation algorithm is tested using a combination of simulated and real measurements. These tests are conducted using …
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Faculty Publications
A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled …