Feature based robot navigation: using fuzzy logic and interval analysis

This work describes a new approach for mobile robot navigation using interval analysis and fuzzy logic. The robot is equipped with inertial sensors, encoders and ultrasonic sensors. The map used for this study is two-dimensional and it is assumed to be known. Multiple sensor fusion for robot localisation and navigation has attracted a lot of interested in recent years. The most commonly used approach is based on Kalman filter and other stochastic filters. Here we propose an alternative approach using interval analysis with multiple sets of ultrasonic measurements. Interval analysis has been already successfully applied in the past for robot localisation. But the results obtained may be conservative. Therefore this approach is extended using multiple sets of ultrasonic measurements, which results in estimation of multiple interval robot positions. These multiple interval robot positions are then fused using fuzzy logic to give a less conservative interval robot position estimate. Also interval analysis based algorithm can be used only in the presence of land marks. This problem is overcome here using additional sensors such as encoders and inertial sensors, which gives an estimate of the robot position using fuzzy logic in the absence of land marks.