This work addresses the problem of indoor state estimation for autonomous flying vehicles with an optic flow approach. The paper discusses a sensor configuration using six optic flow sensors of the computer mouse type augmented by a three-axis accelerometer to estimate velocity, rotation, attitude and viewing distances. It is shown that the problem is locally observable for a moving vehicle. A Kalman filter is used to extract these states from the sensor data. The resulting approach is tested in a simulation environment evaluating the performance of three Kalman filter algorithms under various noise conditions. Finally, a prototype of the sensor hardware has been built and tested in a laboratory setup. Paper published: Verveld, M.J., Chu, Q.P., De Wagter, C. and Mulder, J.A. “Optic Flow Based State Estimation for an Indoor Micro Air Vehicle” AIAA Guidance, Navigation, and Control Conference, August 2010, Toronto, Canada AIAA 2010-8209, DOI: 10.2514/6.2010-8209