Localization of a tracked robot based on fuzzy fusion of wheel odometry and visual odometry in indoor and outdoor environments

Tracked robots usually have poor localization performance because of slippage of their tracks. This study proposes a new localization method for tracked robots that uses fuzzy fusion of stereo-camera-based visual odometry and encoder-based wheel odometry. Visual odometry can be inaccurate when an insufficient number of visual features are available, while the encoder is prone to accumulating errors when large slips occur. To combine these two methods, the weight of each method was controlled by a fuzzy decision depending on the surrounding environment. The experimental results show that the proposed scheme improved the localization performance of a tracked robot.