Dead-reckoning via encoders on wheeled-mobile robots is a simple but inaccurate method to estimate position. The major drawback of encoders is wheel slippage errors that accumulate over time. This problem is often addressed by using additional sensors such as compass, gyroscope, or GPS. This paper details the integration and effectiveness of a relatively low-cost solution using an electronic compass to reduce positioning error on a wheeled tricycle mobile robot. A customised Visual Studio program has been developed to adjust the settings of the electronic compass and integrate it with the Visual Studio based robot control system. The electronic compass heading data is fused with the encoder odometry heading data in three different ways: simple fusion, linear weighted fusion, and Kalman filter fusion. Simple fusion and linear weighted fusion rely on parameters determined from angular acceleration and angular velocity, respectively. The Kalman filter uses variance data for the encoders and electronic compass to determine an optimal heading. Experiments have been conducted in an indoor corridor environment to evaluate and compare the various fusion methods. Position error is successfully reduced and is sufficient to locate the robot within the corridor.