挖掘机动力臂挖掘轨迹规划方法研究

发布时间：2018-05-28 23:51

本文选题：D-H矩阵 + 轨迹规划　；参考：《太原科技大学》2017年硕士论文

【摘要】：挖掘机轨迹规划是当前挖掘机智能化发展的重要方向,也是实现轨迹控制的第一步。轨迹规划是指在挖掘机执行工作任务前,根据已知信息如铲斗齿尖必经过的点和对应的挖掘机姿态,规划挖掘机工作时工作装置各个时刻的姿态。轨迹规划需要同时保证运行过程平稳,可靠。本文通过研究轨迹规划研究现状和挖掘机正、逆运动学问题,提出了将铲斗齿尖轨迹和挖掘后角作为决策变量的自主智能规划方法,并围绕这一方法进行了理论分析和实验验证。通过标准D-H运动学坐标表示方法,研究挖掘机逆运动学问题的求解方法,提出一种智能间接求逆方法。这种间接方法能够结合主流智能算法求解挖掘机逆运动学问题,将三维搜索转变为一维搜索,简化了计算过程,使计算更加直观。以遗传算法为例求解逆运动学问题,说明了间接算法的优点。分析现有规划方法的优缺点,在间接求逆方法的基础上,提出一种能够与挖掘目标建立数学关系的智能规划算法,以挖掘力、斗容及铲斗干涉程度为优化目标,不断选择最优齿尖轨迹函数和挖掘后角变化函数,最终使得挖掘轨迹符合挖掘过程中的挖掘力、斗容和干涉要求,并且不产生铲斗与轨迹的干涉。以遗传算法作为其中的之智能算法,在Matlab平台仿真实验,并与传统方法比较,总结自主智能算法在实用性上的优点。以挖掘机模型为基础,搭建实验平台,安装传感器,将挖掘机变为电控,并能实时获取油缸伸出量,形成带闭环反馈的片上控制系统硬件。研究IIC通信方式及应用办法,以Qt为集成开发环境编写相应的控制软件,MySQL数据库为媒介,编成能在嵌入式Linux系统上应用的挖掘机控制系统软件。最终,以上述实验平台为基础,选取两个代表性工况,用自主遗传轨迹规划方法计算轨迹并实验验证。实验得出结论,智能规划方法解决了基本的运动学问题。
[Abstract]:The trajectory planning of excavator is an important direction of intelligent development of excavator and the first step to realize trajectory control. Trajectory planning refers to the posture of the excavator's working device at every time according to the known information such as the point through which the bucket tooth tip must pass and the corresponding excavator attitude before the excavator carries out its work task. Trajectory planning needs to ensure the smooth and reliable operation process at the same time. In this paper, by studying the current situation of trajectory planning and the forward and inverse kinematics of excavators, an autonomous intelligent planning method is proposed, in which the trajectory of bucket tip and the angle of excavating are taken as decision variables. Theoretical analysis and experimental verification are carried out around this method. Based on the standard D-H kinematic coordinate representation method, the method of solving the inverse kinematics problem of excavator is studied, and an intelligent indirect inverse method is proposed. This indirect method can solve the inverse kinematics problem of excavator by combining with the mainstream intelligent algorithm, and can transform 3D search into one-dimensional search, which simplifies the calculation process and makes the calculation more intuitive. Taking genetic algorithm as an example to solve inverse kinematics problem, the advantages of indirect algorithm are illustrated. Based on the analysis of the advantages and disadvantages of the existing planning methods, an intelligent planning algorithm, which can establish mathematical relations with the mining targets, is proposed on the basis of indirect inverse methods. The optimal targets are mining force, bucket capacity and bucket interference degree. The optimal tooth tip trajectory function and the change function of the rear angle of mining are chosen continuously, which makes the mining track meet the requirements of mining force, bucket capacity and interference, and does not produce the interference of bucket and trajectory. With genetic algorithm as one of the intelligent algorithms, the simulation experiments on Matlab platform are carried out, and compared with the traditional methods, the advantages of autonomous intelligent algorithm in practicability are summarized. Based on the model of excavator, the experiment platform is built, the sensor is installed, the excavator can be changed into electric control, and the oil cylinder can be obtained in real time, and the hardware of the on-chip control system with closed-loop feedback can be formed. The communication mode and application method of IIC are studied. The software of excavator control system which can be used in embedded Linux system is programmed by using QT as the integrated development environment and the corresponding control software of IIC database as the medium. Finally, based on the above experimental platform, two representative working conditions are selected, and the trajectory is calculated by autonomous genetic trajectory planning method and verified by experiments. The experimental results show that the intelligent planning method solves the basic kinematics problem.
【学位授予单位】：太原科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU621

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