Vision-based system of AUV for an underwater pipeline tracker

This paper describes a new framework for detection and tracking of underwater pipeline,which includes software system and hardware system.It is designed for vision system of AUV based on monocular CCD camera.First,the real-time data flow from image capture card is pre-processed and pipeline features are extracted for navigation.The region saturation degree is advanced to remove false edge point group after Sobel operation.An appropriate way is proposed to clear the disturbance around the peak point in the process of Hough transform.Second,the continuity of pipeline layout is taken into account to improve the efficiency of line extraction.Once the line information has been obtained,the reference zone is predicted by Kalman filter.It denotes the possible appearance position of the pipeline in the image.Kalman filter is used to estimate this position in next frame so that the information of pipeline of each frame can be known in advance.Results obtained on real optic vision data in tank experiment are displayed and discussed.They show that the proposed system can detect and track the underwater pipeline online,and is effective and feasible.     

Object detection and tracking method of AUV based on acoustic vision

This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.     

AUV Local Path Planning Based on Acoustic Image Processing

The forward-looking image sonar is a necessary vision device for Autonomous Underwater Vehicles （AUV）. Based on the acoustic image received from forward-looking image sonar, AUV local path is planned. When the environment model is made to adapt to local path planning, an iterative algorithm of binary conversion is used for image segmentation. Raw data of the acoustic image, which were received from serial port, are processed. By the use of ＂Mathematic Morphology＂ to filter noise, a mathematic model of environment for local path planning is established after coordinate transformation. The optimal path is searched by the distant transmission （Dt） algorithm. Simulation is conducted for the analysis of the algorithm. Experiment on the sea proves it reliable.