水下无人航行器机械手系统动力学建模与协调运动轨迹优化  

Dynamic Modeling and Coordinate Motion Trajectory Optimization for Underwater Vehicle and Manipulator System

作　　者：黄海[1] 张国成[1] 杨溢[1] 

机构地区：[1]哈尔滨工程大学水下机器人技术重点实验室,哈尔滨150001

出　　处：《上海交通大学学报》2016年第9期1437-1443,1451,共8页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目项目(51209050;51579053);教育部博士点基金(20122304120003)

摘　　要：针对水下无人航行器和机械手系统,研究了动力学建模与协调运动的轨迹优化技术.基于水下无人航行器和机械手系统的运动学模型,使用Newton-Eulerian方法反向递推得到系统的动力学模型,系统分析了恢复力矩和耦合作用力,并以动力学模型为基础,通过对偶原理结合遗传算法建立了水下无人航行器和机械手系统协调运动的轨迹优化算法.仿真结果表明,在没有协调运动轨迹优化和航行器姿态控制的情况下,手臂的俯仰和摆动对航行器产生比较大的影响,所建立的协调运动轨迹优化算法通过航行器和机械手协调运动较大地减小了作业过程中恢复力矩对航行器的作用,使得航行器具有更多的控制力保持作业中的姿态并应付外界扰动,通过和微粒群算法的比较证明了该算法的优越性.The dynamic model and coordinate motion trajectory optimization have been investigated on un- manned underwater vehicle and manipulator system. Based on the kinematic model of underwater vehicle and manipulator system, the dynamic model has been obtained using the Newton-Eulerian recursive algo- rithm, and the restoring and coupling reaction forces have been systematically analyzed. Furthermore, a motion trajectory optimization algorithm has been designed in combination with primal-dual optimization and the genetic algorithm based on dynamic analysis. Simulations results display that the pitch and swing of manipulator has a great effect on the vehicle. Restoring forces have been greatly reduced by the optimi- zation algorithm. Therefore, more thrust force will be available for oceanic disturbance. The comparison results illustrate that the genetic algorithm outperforms the particle swarm optimization algorithm in traj- ectory optimization.

关 键 词：水下无人航行器 机械手 动力学建模 运动轨迹优化 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]