Modeling and simulation of FLC-based navigation algorithm for small gas pipeline inspection robot

Pipeline robot are widely used since pipelines require to be inspected regularly for leakages caused by natural disaster, etc. Most robots which rely heavily on manual operation are incapable of self-navigation in pipe. Moreover incorrect operations would degrade the efficiency, and sometimes damage the robots especially when they pass through elbows or junctions. Some robots can realize navigation based on multi-sensor such as position sensitive detector and laser sensor, but navigation performance for such robots will be greatly influenced by the performance of these sensors, and space to install large number of sensors is limited. In this study, we propose an approach of pipeline robot's navigation based on fuzzy logic control (FLC) algorithm for passing through elbows or T-junctions. A CCD camera installed on the robot is used for locating region of interest (ROI) in elbow or junction. Moreover, ROIs formed by reflection of robot's LED light and edge of pipe's dark hole are considered as input variables in the FLC system. By analyzing system outputs, we can control the robot's speed and yaw angle in real time. Compared with conventional studies on pipeline robot's navigation method, the proposed method can be more precise and faster by using FLC algorithm and analyzing ROI with fewer sensors. Finally, we conducted a simulation validation, and the results showed that the robot was capable of adapting to known pipe environments and realizing navigation in straight part, elbow, and junction of pipe.