Sensor Fusion Map Building-Based on Fuzzy Logic Using Sonar and SIFT Measurements

This article presents a sensor data fusion method that can be used for map building. This takes into account the uncertainty inherent in sensor measurements. To this end, fuzzy logic operators are used to fuse the sensory information and to update the fuzzy logic maps. The sensory information is obtained from a sonar array and a stereo vision system. Features are extracted using the Scale Invariant Feature Transform (SIFT) algorithm. The approach is illustrated using actual measurements from a laboratory robot.