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1.
PUMA机械手逆运动方程新的推导方法及求解   总被引:19,自引:0,他引:19  
本文提出了一种新的推导PUMA型机器人逆运动方程的方法,进而给出逆运动问题新的求解方法.此方法不需要对机械手末端位姿进行坐标变换,而且也给出了问题的解析解.另外在解的推导过程中避免了大量的逆矩阵相乘.方法简单.仿真证明了计算结果的正确.  相似文献   

2.
针对7自由度冗余机器人实时运动控制,对机器人逆运动学提出了一种新的求解方法.采用位姿分解方式,使7自由度冗余机器人逆运动学简化为4自由度位置逆运动学求解.在梯度投影法得到位置优化解的基础上,利用机器人封闭解公式求得一组优化解.通过对7自由度机器人仿真分析,表明了该方法的有效性.  相似文献   

3.
旋转输入型并联机器人位置逆解分析的轨迹圆法   总被引:2,自引:0,他引:2  
徐文军  孙立宁  安辉  蔡鹤皋 《机器人》1998,20(5):368-372
本文分析了几种典型旋转输入型并联机器人的机构形式和特点,提出了适用于各种旋转输入型并联机器人位置逆解分析的轨迹圆法,利用该方法可方便地进行位置逆解建模与求解、逆解情况(有无解及多解性)判断等,简化了位置控制算法  相似文献   

4.
一种运动旋量逆解子问题的求解及其应用   总被引:2,自引:0,他引:2  
赵杰  刘玉斌  蔡鹤皋 《机器人》2005,27(2):163-167
旋量理论在机器人运动学逆解过程中将运动方程分解为若干子问题,目前常见的子问题组合并不能完成所有机器人的逆解问题.本文提出了在机器人逆解过程中会遇到的另一种子问题的解法,并给出构造该子问题的限定条件.运用该解法,给出具有RTS运动链并联机器人的运动学逆解方法,并归纳出利用未知量组中对参考点起相同作用的旋量组合来简化计算的方法.该子问题的解决扩充、便利了旋量理论在机器人运动学逆解中的应用.  相似文献   

5.

针对-自由度冗余机器人实时运动控制,对机器人逆运动学提出了一种新的求解方法.采用位姿分解方式,使-自由度冗余机器人逆运动学简化为,自由度位置逆运动学求解.在梯度投影法得到位置优化解的基础上,利用机器人封闭解公式求得一组优化解.通过对-自由度机器人仿真分析,表明了该方法的有效性.

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6.
张纪元  牛志纲 《机器人》1999,21(4):256-259
对于含螺旋副(H)的空间连杆机构或机器人机构,无 法用有理化法将其分析与综合方程组化成多项式方程组,因而不能用精确同伦法求解这些 机构的多解问题.本文提出近似同伦法并用该法首次解决了空间7H连杆机构的装配构形问题 .本文方法适用于求解任何含H副的空间连杆机构或机器人机构的多解问题.  相似文献   

7.
机器人运动学反解中的奇异点处理   总被引:5,自引:0,他引:5  
朱向阳  熊有伦 《机器人》1996,18(5):264-267
本文研究机器人运动学反解中的奇异点处理问题,给出了机器人微分运动Jacobian矩阵J(q)条件数的一个上界,并在此基础上提出机器人关节速度阻尼伪逆解方法中阻尼系数的一种自适应调整方法,该方法可以保证在奇异点附近伪逆解的稳定性。  相似文献   

8.
新型6-HTRT并联机器人工作空间和参数研究   总被引:8,自引:0,他引:8  
于晖  孙立宁  刘品宽  蔡鹤皋 《机器人》2002,24(4):293-298
本文介绍了新型6-HTRT并联机器人的机构型式和工作原理,给出了考虑到约束条件的 位置逆解算法和存在多组解时的逆解选取准则.利用逆解算法和三维搜索,得到了确定该类 型机器人工作空间的方法和工作空间体积的计算公式.分析了6-HTRT并联机器人工作空间 的形态特点以及机器人结构参数和运动参数对工作空间体积的影响.  相似文献   

9.
基于神经网络的机器人位姿逆解   总被引:5,自引:0,他引:5  
张伟 《机器人》1997,19(2):151-154,160
本文运用神经网络求解机器人运动学位姿逆解,突破了文献局限于研究位置逆解的状况,首次实现自组织神经网络求解机器人姿态逆解。  相似文献   

10.
周芳芳  樊晓平  赵颖 《计算机工程》2006,32(14):193-195
机器人逆运动学求解的可视化算法包含两部分,数值求解两个(或一个)非线性方程和4(或5)自由度机器人封闭解,实现了任意结构的6自由度机器人的逆运动学方程的求解,根据D-H参数表生成机器人三维模型实现机器人结构的可视化,有效地判断逆解的合理性,并为机器人学习提供了辅助工具。  相似文献   

11.
针对一类冗余自由度超声检测机器人的传统逆运动学求解算法耗时长且准确度低的问题,提出了一种基于集合划分和解析解法相结合的逆运动学求解算法。首先采用De-navit-Hartenberg方法建立检测机器人的运动学方程;其次,利用解析解法求出机器人逆解的解析表达式,并提出三种自由度分配方案;最后,选择合适的自由度分配方案,据此对超声波探头位姿集合作划分,结合逆解解析式求出运动学逆解。实际应用中,借助十一轴超声波检测机器人,利用该算法对具有复杂外形的飞机螺旋桨叶片进行检测。结果表明,与传统的纯数值解法相比,该算法能够快速得到精确的运动学逆解。  相似文献   

12.
为了提高电力系统的自动化水平,减轻电力工人在检修高压输电系统时的劳动强度,同时保障电力工人人身安全,提出并设计一种可以攀爬电力铁塔的六自由度关节式机器人,针对该构型进行运动学分析和求解.为解决传统的解析法用于机械臂逆运动学求解过程中存在操作繁琐和奇异点无法逆运算等问题,提出一种基于改进天牛须算法的电力攀爬机器人运动学逆解算法.首先,对电力攀爬机器人进行DH建模,得到正运动学方程;然后,使用正运动学方程和目标位姿建立代价函数,采用改进天牛须算法对代价函数优化;最后,使用Matlab实现此算法进行仿真验证.实验结果表明,与传统的天牛须算法、改进遗传算法以及改进粒子群算法相比,所提出算法具有较好的收敛性,求解精度较高.  相似文献   

13.
Computer generation of symbolic solutions for the direct and inverse robot kinematics is a desired capability not previously available to robotics engineers. In this article, we present a methodology for the design of a software system capable of solving the direct and inverse kinematics for n degree of freedom (dof) manipulators in symbolic form. The inputs to the system are the Denavit-Hartenberg parameters of the manipulator. The outputs of the system are the direct and inverse kinematics solutions in symbolic form. The system consists of a symbolic processor to perform matrix and algebraic manipulations and an expert system to solve the class of nonlinear equations involved in the solution of the inverse kinematics problem. The system can be used to study robot kinematics configurations whose inverse kinematics solutions are not known to exist a priori. Two examples are included to illustrate its capabilities. The first example provides explicit analytical solutions, previously believed nonexistent, for a 3 dof manipulator. A second example is included for a robot whose inverse kinematics solution requires intensive algebraic manipulations.  相似文献   

14.
V01弧焊机器人运动学反解及臂形标志的确定   总被引:2,自引:0,他引:2  
崔鲲  孙论强 《机器人》1997,19(6):444-449
为了对V01弧焊机器人深层次的开发,需要首先剖析其运动学模型,求解的反臂形问题。本文利用几何解法,针对V01弧焊机器人建立了相应的逆运动学算法,解决了求解臂形标志问题,从而为V01弧焊机器人的离线编程打上了基础。  相似文献   

15.
6R机器人实时逆运动学算法研究   总被引:4,自引:0,他引:4  
提出一套解决各类6R机器人逆运动学问题的实时算法. 一般算法通过矢量计算和16阶矩阵分解得到一般6R机器人的最多16组逆运动学解. 封闭解法直接提取运动学等式求出关节变量的解析解. 组合算法将封闭解法或一般算法的结果作为初始值, 采用牛顿-拉夫森方法迭代出逆运动学精确解, 适用于所有接近满足封闭解条件或一般算法条件的6R机器人. 求解实验结果表明, 整套算法最大算法时间约为2.03 ms, 为任意几何结构的6R机器人应用于强实时系统提供了逆运动学解决方案.  相似文献   

16.
The neural-network-based inverse kinematics solution is one of the recent topics in the robotics because of the fact that many traditional inverse kinematics problem solutions such as geometric, iterative and algebraic are inadequate for redundant robots. However, since the neural networks work with an acceptable error, the error at the end of inverse kinematics learning should be minimized. In this study, simulated annealing (SA) algorithm was used together with the neural-network-based inverse kinematics problem solution robots to minimize the error at the end effector. The solution method is applied to Stanford and Puma 560 six-joint robot models to show the efficiency. The proposed algorithm combines the characteristics of neural network and an optimization technique to obtain the best solution for the critical robotic applications. Three Elman neural networks were trained using separate training sets and different parameters, since one of them can give better results than the others can. The best result is selected within three neural network results by computing the end effector error via direct kinematics equation of the robotic manipulator. The decimal part of the neural network result was improved up to 10 digits using simulated annealing algorithm. The obtained best solution is given to the simulated annealing algorithm to find the best-fitting 10 digits for the decimal part of the solution. The end effector error was reduced significantly.  相似文献   

17.

Geometric inverse kinematics procedures that divide the whole problem into several subproblems with known solutions, and make use of screw motion operators have been developed in the past for 6R robot manipulators. These geometric procedures are widely used because the solutions of the subproblems are geometrically meaningful and numerically stable. Nonetheless, the existing subproblems limit the types of 6R robot structural configurations for which the inverse kinematics can be solved. This work presents the solution of a novel geometric subproblem that solves the joint angles of a general anthropomorphic arm. Using this new subproblem, an inverse kinematics procedure is derived which is applicable to a wider range of 6R robot manipulators. The inverse kinematics of a closed curve were carried out, in both simulations and experiments, to validate computational cost and realizability of the proposed approach. Multiple 6R robot manipulators with different structural configurations were used to validate the generality of the method. The results are compared with those of other methods in the screw theory framework. The obtained results show that our approach is the most general and the most efficient.

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18.
In robotics, inverse kinematics problem solution is a fundamental problem in robotics. Many traditional inverse kinematics problem solutions, such as the geometric, iterative, and algebraic approaches, are inadequate for redundant robots. Recently, much attention has been focused on a neural-network-based inverse kinematics problem solution in robotics. However, the result obtained from the neural network requires to be improved for some sensitive tasks. In this paper, a neural-network committee machine (NNCM) was designed to solve the inverse kinematics of a 6-DOF redundant robotic manipulator to improve the precision of the solution. Ten neural networks (NN) were designed to obtain a committee machine to solve the inverse kinematics problem using separately prepared data set since a neural network can give better result than other ones. The data sets for the neural-network training were prepared using prepared simulation software including robot kinematics model. The solution of each neural network was evaluated using direct kinematics equation of the robot to select the best one. As a result, the committee machine implementation increased the performance of the learning.  相似文献   

19.
The solution of inverse kinematics problem of redundant manipulators is a fundamental problem in robot control. The inverse kinematics problem in robotics is the determination of joint angles for a desired cartesian position of the end effector. For the solution of this problem, many traditional solutions such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. Furthermore, many neural network approaches have been done to this problem. But the neural network-based solutions are not much reliable due to the error at the end of learning. Therefore, a reliability-based neural network inverse kinematics solution approach has been presented, and applied to a six-degrees of freedom (dof) robot manipulator in this paper. The structure of the proposed method is based on using three networks designed parallel to minimize the error of the whole system. Elman network, which has a profound impact on the learning capability and performance of the network, is chosen and designed according to the proposed solution method. At the end of parallel implementation, the results of each network are evaluated using direct kinematics equations to obtain the network with best result.  相似文献   

20.
Redundant robots have received increased attention during the last decades, since they provide solutions to problems investigated for years in the robotic community, e.g. task-space tracking, obstacle avoidance etc. However, robot redundancy may arise problems of kinematic control, since robot joint motion is not uniquely determined. In this paper, a biomimetic approach is proposed for solving the problem of redundancy resolution. First, the kinematics of the human upper limb while performing random arm motion are investigated and modeled. The dependencies among the human joint angles are described using a Bayesian network. Then, an objective function, built using this model, is used in a closed-loop inverse kinematic algorithm for a redundant robot arm. Using this algorithm, the robot arm end-effector can be positioned in the three dimensional (3D) space using human-like joint configurations. Through real experiments using an anthropomorphic robot arm, it is proved that the proposed algorithm is computationally fast, while it results to human-like configurations compared to previously proposed inverse kinematics algorithms. The latter makes the proposed algorithm a strong candidate for applications where anthropomorphism is required, e.g. in humanoids or generally in cases where robotic arms interact with humans.  相似文献   

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