基于DIDSON的未知海域覆盖规划算法

A Coverage Path Planning Algorithm Based on DIDSON for Unknown Marine Environment

针对自主水下机器人的路径规划问题,提出一种基于双频识别侧扫声呐(DIDSON)的全局路径规划算法。根据双频识别侧扫声呐的物理特性对AUV进行数学建模,根据声呐的工作频率不同,将AUV分为高频、低频两种工作模式。高频模式下成像精度高,低频模式下成像范围大。文中提出了一种D2-CPP算法,根据声呐返回的识别结果,算法会自主切换AUV的工作模式,并动态规划出对应的路径点,直到覆盖所有区域。通过与割草机算法的仿真对比,证明了算法的有效性,近海实验证明了算法的可靠性。

To solve the path planning problem of autonomous underwater vehicle(AUV),a global path planning algorithm is proposed based on dual-frequency identification side-scan sonar(DIDSON).According to the physical characteristics of the DIDSON sonar,the AUV is mathematically modeled.The AUV is divided into two operating modes:high frequency and low frequency.Moreover,the image in high frequency has a higher precision and the image produced in low frequency mode has a wider range.In this paper,a DIDSON data-driven coverage path planning(D2-CPP)algorithm is proposed.After the recognition results are received by sonar,D2-CPP will switch the working mode of AUV automatically and plan dynamically a set of corresponding path points until all areas are covered.Compared with the lawnmower algorithm,the simulation and offshore experiments show that the algorithm is effective and reliable.