一种混联机器人的运动学及轨迹规划研究

发布时间：2019-03-25 07:30

【摘要】：与串联机构相比,经过合理设计的并联机构,一般具有刚度大、精度高等优点,但由于其闭环结构的特点,会导致工作空间相对较小、末端执行器因姿态角不足而影响加工性能等问题。如今,由少自由度并联机构与其它运动方向串联机构组合所构成的并串联机构成为研究的热点。本文针对一种基于Delta工业机器人的五自由度混联机器人进行研究,此机器人在很大程度上既突破了纯并联机构在工作空间方面的限制,又弥补了纯串联机构在刚度方面的不足。首先,采用螺旋理论分析了混联机器人并联部分的运动性质,并使用K-G修正公式确定了混联机器人的运动自由度;使用D-H法建立了混联机器人的数学模型并推导了混联机器人的逆运动方程;采用空间几何解析法对混联机器人进行了分析,推导了正运动学的解析解;使用MATLAB软件对混联机器人的运动学正反解算法进行了仿真与验证,证明了运动学正反解算法有效可行并可满足工程应用。其次,基于混联机器人并联部分的逆运动学算法,提出采用图解法分析混联机器人并联部分的工作空间,并将结果与蒙特卡洛法生成的工作空间进行对比,验证了图解法分析的正确性;采用图解法分析了串联部分的工作空间以及整个混联机器人的工作空间。再次,简要介绍了机器人轨迹规划概念及相关理论;在关节空间中重点比较了三次多项式和五次多项式插值算法,运用MATLAB软件计算运动学反解,并绘制模拟各关节的位置、速度和加速度等曲线;在笛卡尔坐标空间中采用直线及圆弧插补方法对混联机器人进行轨迹规划。最后,在ADAMS/View中验证了添加运动副后的混联机器人自由度数目为五;使用STEP5函数作为驱动函数对混联机器人进行了仿真试验,绘制了混联机器人各关节以及末端点的运动学变化曲线;结果显示,各曲线在中间路径点处平滑无突变,验证了所推导的运动学算法的正确性,也验证了五次多项式插值算法能保证混联机器人仿真过程运行平稳,这将有助于减少对电机的损害,从而延长混联机器人使用寿命,并且为轨迹规划控制的进一步研究提供了理论基础。
[Abstract]:Compared with series mechanism, the reasonably designed parallel mechanism usually has the advantages of large stiffness and high precision, but because of its closed-loop structure, the workspace is relatively small. Due to the lack of attitude angle, the processing performance of the end-effector is affected. Nowadays, the parallel series mechanism which is composed of the combination of the parallel mechanism with less degrees of freedom and the series mechanism in other directions of motion has become a hot topic in the field of research. In this paper, a five-degree-of-freedom hybrid robot based on Delta industrial robot is studied. To a great extent, this robot not only breaks through the limitation of workspace of pure parallel mechanism, but also makes up for the deficiency of stiffness of pure series mechanism. Firstly, the motion property of the parallel part of the hybrid robot is analyzed by using the screw theory, and the motion freedom of the hybrid robot is determined by the KG correction formula. In this paper, the mathematical model of hybrid robot is established by using DH method, and the inverse motion equation of hybrid robot is deduced, and the analytic solution of forward kinematics is deduced by analyzing the hybrid robot with spatial geometric analysis method. The kinematics forward and inverse solution algorithm of hybrid robot is simulated and verified by using MATLAB software. It is proved that the kinematics forward and inverse solution algorithm is effective and feasible and can satisfy the engineering application. Secondly, based on the inverse kinematics algorithm of the parallel part of the hybrid robot, a graphic method is proposed to analyze the workspace of the parallel part of the hybrid robot, and the results are compared with the workspace generated by the Monte Carlo method. The correctness of graphic analysis is verified. The workspace of the series part and the workspace of the whole hybrid robot are analyzed by graphic method. Thirdly, the concept and related theory of robot trajectory planning are introduced briefly. In the joint space, the interpolation algorithms of cubic polynomial and quintic polynomial are compared emphatically. The inverse kinematics solution is calculated by using MATLAB software, and the curves simulating the position, velocity and acceleration of each joint are drawn. The trajectory planning of hybrid robot is carried out by linear and circular interpolation in Cartesian coordinate space. Finally, it is verified in ADAMS/View that the number of degrees of freedom of the hybrid robot with the addition of motion pairs is five. The STEP5 function is used as the driving function to simulate the hybrid robot, and the kinematic curves of each joint and the end of the hybrid robot are drawn. The results show that each curve has no abrupt change at the intermediate path point, which verifies the correctness of the derived kinematics algorithm, and verifies that the quintic polynomial interpolation algorithm can ensure the smooth operation of the simulation process of the hybrid robot. This will help to reduce the damage to the motor and prolong the service life of the hybrid robot, and provide a theoretical basis for the further study of trajectory planning and control.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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