Simulation Study on Underwater Autonomous Robot Based on Fuzzy Kalman Filter Algorithm

Data fusion methods are widely used in autonomous robots´ measurement system in order to acquire more comprehensive and more exact information. Multi-sensor data fusion is to combine multi-sensor´s information, which is redundant or complementary in the space or the time to obtain the uniform description or the understanding to the measured object according to a certain criterion. Move-in-mud robot is an autonomous robot, which can excavate hole in the mud underwater. It can be used in sunken wreck salvage to improve the efficiency of excavating the hole. Location system of move-in-mud robot is designed in the paper and location principle of move-in-mud robot is analyzed. Fuzzy Kalman filter arithmetic is applied and simulated in location system of move-in-mud robot to fuse redundant information of the robot. The simulation results show the data fusion method can improve location accuracy.