This paper presents a set of algorithms for piloting an autonomous planetary rover along a planned path, performing obstacle avoidance, and improving position estimation. Path-tracking is accomplished using feedback-control of position and orientation errors, measured with respect to the planned path trajectory. Obstacle-avoidance is performed through application of an artificial potential field, to data that can be acquired using a scanning rangefinder. Position and velocity estimation is improved by the algorithmic filtering and fusing of odometry and inertial navigation data streams. Results from computer simulation are used to illustrate the path-tracking and obstacle-avoidance capabilities, and experimental data is used to illustrate how sensor fusion mitigates the effects of wheel-slippage and integration-error in position and velocity estimation.>