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, 37(4): 478-485. DOI: 10.13973/j.cnki.robot.2015.0478
引用本文: 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, 37(4): 478-485. DOI: 10.13973/j.cnki.robot.2015.0478
LI Ye, JIANG Yanqing, ZHANG Guocheng, LI Yiming, CHEN Pengyun. AUV Recovery Path Planning Method Considering Geometrical Constraints[J]. ROBOT, 2015, 37(4): 478-485. DOI: 10.13973/j.cnki.robot.2015.0478
Citation: LI Ye, JIANG Yanqing, ZHANG Guocheng, LI Yiming, CHEN Pengyun. AUV Recovery Path Planning Method Considering Geometrical Constraints[J]. ROBOT, 2015, 37(4): 478-485. 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

  • 摘要: 结合 3 次 B 样条的曲率连续特性和遗传算法的全局搜索特性,提出了一种适合欠驱动 AUV(自治水下机器人)的回收路径规划方法.算法给出连接始末位置的光滑 3 维路径,适用于 AUV 回收的归航阶段,能够保证 AUV 以合适的姿态进行后续的导引对接.首先,分析了 AUV 的欠驱动特性带来的几何约束问题,包括任务终端约束和运动约束.其次,根据 B 样条曲线的特性确定通过选取控制点序列来给出 3 维路径曲线的思路.第一步采用样板的方式确定一部分控制点使曲线满足终端约束条件,第二步将 AUV 的回转和升沉运动约束写入遗传算法,通过对解空间的启发式自适应搜索确定中间控制点,两部分控制点所决定的曲线满足所有的几何约束条件.最后,针对路径的生成和跟踪,设计了半物理动力学仿真试验,从几何的角度对比 AUV 航迹和路径.结果显示,路径与 AUV 的运动能力具有很好的匹配特性,能够保证跟踪结束时 AUV 的位置和姿态满足导引对接阶段的要求.

     

    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.

     

/

返回文章
返回