基于自适应遗传算法的六轴工业机器人时间最优轨迹规划

发布时间：2018-08-12 09:17

【摘要】：作为机器人领域的一个重要分支,工业机器人的发展与应用一直备受社会的关注。随着社会的发展与人们对物质需求的日益增长,工业机器人的作业质量与效率成为人们越来越关心的一个因素。因此,以时间最优为目标的机器人轨迹规划越来越受到学者们的青睐。本文以PUMA560机器人为研究对象,在对其建立运动学模型的基础上,采用五次多项式函数规划出机器人各个关节的运行轨迹,利用一种自适应遗传算法对各关节运动时间进行优化,使机器人在较短的时间内完成规定的动作。本文首先介绍了课题的研究背景和意义以及机器人技术发展状况和应用前景,简要阐述了机器人轨迹规划的一般性问题,并对近年来国内外的专家、学者在机器人轨迹优化方面的研究成果进行调研、综述和分析。根据机器人运动学知识,简要阐述了空间点的描述方法以及坐标变换的理论,并以PUMA560机器人为研究对象,对其建立运动学方程,用各关节变量来表示机器人手臂末端的位姿,并对机器人逆运动学进行分析与求解。通过对机器人轨迹规划理论进行研究,分析了笛卡尔空间中直线插补和圆弧插补的方法,以及关节空间中五次多项式函数和带有抛物线的过渡插值方法。并且通过MATLAB编程分别实现在笛卡尔空间和关节空间中机器人轨迹规划的仿真。在分析遗传算法机理和遗传算子对进化过程影响的基础上,采用一种自适应遗传算法对机器人关节臂的运行轨迹进行优化并通过MATLAB对PUMA560各关节的运行轨迹进行了仿真。对各曲线分析可知,本文的方法较好地实现了时间最优的规划目标,并且保证了各关节的角位移、速度和加速度曲线的平滑,确保机器人平稳、高效地完成任务。
[Abstract]:As an important branch of robot field, the development and application of industrial robot has been paid much attention by the society. With the development of society and the increasing demand for material, the working quality and efficiency of industrial robots have become a more and more concerned factor. Therefore, robot trajectory planning aiming at optimal time is becoming more and more popular. Based on the kinematics model of PUMA560 robot, the fifth order polynomial function is used to plan the trajectory of each joint, and an adaptive genetic algorithm is used to optimize the motion time of each joint. Enables the robot to complete the specified action in a relatively short period of time. This paper first introduces the research background and significance of the subject, the development status and application prospect of robot technology, briefly expounds the general problems of robot trajectory planning, and discusses the experts at home and abroad in recent years. The research results of robot trajectory optimization are summarized and analyzed. According to the kinematics knowledge of the robot, the description method of the space point and the theory of coordinate transformation are briefly expounded. The kinematics equation is established for the PUMA560 robot, and the position and pose of the end of the robot arm are represented by the joint variables. The inverse kinematics of the robot is analyzed and solved. Based on the research of robot trajectory planning theory, the methods of straight line interpolation and arc interpolation in Cartesian space are analyzed, as well as the fifth degree polynomial function and the transitional interpolation method with parabola in joint space. The simulation of robot trajectory planning in Cartesian space and joint space is realized by MATLAB programming. On the basis of analyzing the mechanism of genetic algorithm and the influence of genetic operator on the evolution process, an adaptive genetic algorithm is used to optimize the trajectory of robot joint arm, and the trajectory of each joint of PUMA560 is simulated by MATLAB. According to the analysis of each curve, the method in this paper can achieve the optimal planning goal of time, and ensure the smooth angular displacement, velocity and acceleration curve of each joint, and ensure the robot to finish the task smoothly and efficiently.
【学位授予单位】：安徽工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242.2

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