Research Of Autonomous Navigation Based On Information Filter For AUV

Autonomous Underwater Vehicle (AUV) is an important tool for human todevelop the ocean and has broad prospects. Meanwhile, it faces many technicalchallenges and navigation is one of them. Many of the current navigation approachesrequire GPS, baseline or other equipments while some approaches need priori map,which seriously limits the application of AUV in unknown large-scale underwaterenvironment. Simultaneous Localization and Mapping (SLAM) can help AUVnavigate autonomously, and is a hot button in the research field of AUV. Acquiringenvironmental information by sensors is the first step to solve the SLAM problem,and the more accurate the environment is described, the greater the amount of data is,as a result, the efficiency decreases. Based on these reasons, this paper addresses anautonomous navigation method based on Sparse Extended Information Filter (SEIF)SLAM combined with sensors’ data pre-processing.First, this paper introduces the research situation and development prospects ofthe AUV and SLAM algorithm briefly. And the current mainstream SLAM algorithmsare compared. Then the basic principle and implementation of EKF-SLAM which oneof is the most widely used SLAM algorithms are presented. This paper focuses on theSEIF-SLAM which is the information form of EKF. After analyzing the advantagesand disadvantages of different sonar, the single-beam scanning sonar is chosen in thispaper. Based on the working principle of this sonar, sonar data preprocessing methodsincluding denoising, sparsification and correction are used to improve the navigationaccuracy and performance of real-time of AUV further.Actual data of sea trials in Tuandao Bay are used to verify the feasibility of theproposed navigation algorithm and data preprocessing methods. The results andanalysis show that the algorithm based on SEIF-SLAM behaves better in the estimateof AUV position and orientation compared with conventional methods, while datapreprocessing improves the validity and accuracy of the AUV navigation further.Finally, this paper summaries the work and pointes out the research direction in thefuture.