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Orientation estimation plays a crucial role in robotics. Precise and reliable estimation of orientation, and the yaw angle in particular, is still a challenge and subject of great concern among researchers. This paper presents the development of a platform for yaw angle estimation by fusing inertial and magnetic sensing (a low-cost multi-sensorial system composed by both a digital compass and a gyroscope). A Kalman filter is used to estimate the error produced by the gyroscope. Experimental results indicate that the proposed solution is able to eliminate the drift effect produced by gyroscope data and, at the same time, has the capacity to react to fast orientation changes.