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考虑几何约束的AUV回收路径规划

李晔 姜言清 张国成 李一鸣 陈鹏云

机器人Issue(4):478-485,8.
机器人Issue(4):478-485,8.DOI:10.13973/j.cnki.robot.2015.0478

考虑几何约束的AUV回收路径规划

AUV Recovery Path Planning Method Considering Geometrical Constraints

李晔 1姜言清 1张国成 1李一鸣 1陈鹏云1

作者信息

  • 1. 哈尔滨工程大学水下机器人技术重点实验室,黑龙江 哈尔滨 150001
  • 折叠

摘要

Abstract

Combining the curvature continuous feature of cubic B-spline and the superior global search performance of genetic algorithm, a docking path planning method suitable for underactuated AUV (autonomous underwater vehicle) is designed. A smooth 3-dimensional path from the start point to the end point is given for the homing stage in AUV recovery, by which appropriate AUV position and attitude required by the following guided docking stage are guaranteed. Firstly, geometrical constraints caused by underactuated AUV are analyzed, including terminal constraint and kinematical constraint. Secondly, an idea of determining 3-D path by selecting control points sequence is presented according to the features of B-spline curves. In the first step, some control points are selected through analyzing mission terminal constraints in template pattern. In the second step, the control points in the middle section are given out after adaptive heuristic search in the solution space by using gene algorithm, whose fitness function contains constraints of AUV motion like rotation and heaving respectively in horizontal and vertical plane. The curve defined by the previous two sections of control points finally satisfies all geometrical constraints. At last, semi-physical dynamical simulation experiments on path generation and tracking are carried out. The tracking result shows that the geometrical character of path matches the maneuverability of AUV. Position and attitude of AUV are suitable for the following guided docking stage while path tracking finished.

关键词

路径规划/欠驱动AUV/水下回收/遗传算法/B样条

Key words

path planning/underactuated AUV/underwater recovery/genetic algorithm/B-spline

分类

信息技术与安全科学

引用本文复制引用

李晔,姜言清,张国成,李一鸣,陈鹏云..考虑几何约束的AUV回收路径规划[J].机器人,2015,(4):478-485,8.

基金项目

国家自然科学基金项目(51279221,51179035);中国博士后科学基金面上资助项目(2014M561333). ()

机器人

OA北大核心CSCDCSTPCD

1002-0446

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