Simultaneous Multi-sonars Detection And Patrolling Control Using UUV For Unknown Environment

Two main issues for unknown environment detection using Underwater UnmannedVehicle (UUV) is orientation underwater and the control method. In this paper, aSimultaneous Detection and Patrolling (SDAP) control algorithm is proposed. Multi rangesonars are effective equipment for collecting information underwater, but the confidencecannot satisfy the control requirement, therefore, weak reliability for range sonar data isrevealed obviously. Unmanned characteristic during UUV implementing mission requirecognition and understanding ability more accuracy, especially synchronism betweenperception and patrolling exists mutual exclusion. Therefore, considering weak reliabilitysonar data and UUV characteristic, pretreatment for sonar data, contour reconstruction forunknown environment, path smoothness, decision under local environment and patrollingcontrol are studied as follows.1. To solve the problem that low confidence of multi range sonar data collected inunderwater complex environment cannot satisfy path requirement of patrolling control,wavelet transform is introduced to pretreatment sonar data. Compared to normal data in theset, singular data is regards as high frequency. Local amplify ability of wavelet transform leadto its introduction for data pretreatment. Owing to environment contour constructed usingpretreatment data is treated to be the reference information for patrolling path; its successionmust be guaranteed. To complement data denoted by singular point, the estimation value atcorresponding time is calculated.2. To achieve contour through clustering data with same property on the basis ofpretreatment data and eliminating the singular data out of data bound. Considering supportvector algorithm can implement the function above and satisfy real time requirement forapplication to be reference for patrolling control, it is introduced to realize reconstructionprocess. In addition, to ensure the property of singular data detected at first time, inertiaalgorithm is proposed to improve SVC method. Combined data confidence and DopplerVelocity Lopper (DVL) information, unknown environment contour based on weak reliabilitymulti range sonar data can be reconstructed.3. According to the characteristic of UUV and the requirement for controller design,smoothness desired path for patrolling control is constructed and automatic decision withlocal environment characteristic is present. On the one side, different orders’ Bézier curves areintroduced to fit contour assembled by lines using SVC, to satisfy inertia character for vehicle underwater. On the other side, towards exploration automatically, contour reconstruction andpatrolling must evolve simultaneously, therefore, it is intuitive that automatic decision methodbase on vehicle state and local environment is studied.4. Feedback linearize algorithm is utilized to design controllers for unknownenvironment detection. According to mission requirements, it is separated to two stages:precise following with known path and patrolling control. Two different algorithms offeedback linearize, differential geometry feedback linearize and stable inversion, are justcorresponding to two control stage requirements. In this paper, on one side, a rolling pathgenerator is present to guide vehicle to follow preset path with arbitrarily initial state,including orientation and position, and differential geometry feedback linearize method isapplied to control vehicle following precisely. On the other side, stable inversion method withcontour as desired path is introduced to obtain stable input of vehicle in patrolling process.Considering patrolling in real time, it is proposed that desired path in finite time window isregards as input items of the algorithm, and the parameter is optimized to guarantee thesynchronism between detection mission and following control.To verify the effectiveness of contour reconstruction method and patrolling controlalgorithm, simulation and experiment using sea trial data are designed. Validation flows areclarified in detail. Sonar model and the background environment models are established.Evaluate criterions and analysis method for reconstruction and patrolling control algorithmsare present respectively to complete the analysis. The feasibilities of reconstruction methodand patrolling control algorithm are verified through simulation and experiment using realdata from sea trial.