Rover localization results for the FIDO rover

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Abstract
This paper describes the development of a two-tier state estimation approach for NASA/JPL's FIDO Rover that utilizes wheel odometry, inertial measurement sensors, and a sun sensor to generate accurate estimates of the rover's position and attitude throughout a rover traverse. The state estimation approach makes use of a linear Kalman filter to estimate the rate sensor bias terms associated with the inertial measurement sensors and then uses these estimated rate sensor bias terms to compute the attitude of the rover during a traverse. The estimated attitude terms are then combined with the wheel odometry to determine the rover's position and attitude through an extended Kalman filter approach. Finally, the absolute heading of the vehicle is determined via a sun sensor which is then utilized to initialize the rover's heading prior to the next planning cycle for the rover's operations. This paper describes the formulation, implementation, and results associated with the two-tier state estimation approach for the FIDO rover.
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