This paper describes recent work undertaken at the Jet Propulsion Laboratory in Pasadena, CA in the area of increased rover autonomy for planetary surface operations. The primary vehicle for this work is the Field Integrated, Design and Operations (FIDO) rover. The FIDO rover is an advanced technology prototype that is a terrestrial analog of the Mars Exploration Rovers (MER) being sent to Mars in 2003. We address the autonomy issue through improved integration of rover based sensing and higher level onboard planning capabilities. The sensors. include an inertial navigation unit (INU) with 3D gyros and accelerometers, a sun sensor, mast and body mounted imagery, and wheel encoders. Multisensor fusion using an Extended Kalman Filter (EKF) approach coupled with pattern recognition and tracking algorithms has enabled the autonomy that is necessary for maximizing science data return while minimizing the number of ground loop interactions. These algorithms are coupled with a long range navigation algorithm called ROAMAN (Road Map Navigation) for an integrated approach to rover autonomy. We also report the results of algorithm validation studies in remote field trials at Black Rock Summit in Central Nevada, California's Mojave Desert, and the Arroyo Seco at JPL.