首页> 外文期刊>International Journal of Advanced Robotic Systems >Improved Inverse Kinematics Algorithm Using Screw Theory for a Six-DOF Robot Manipulator
【24h】

Improved Inverse Kinematics Algorithm Using Screw Theory for a Six-DOF Robot Manipulator

机译:利用螺杆理论改进了六-DOF机器人机械手的逆运动学算法

获取原文
获取原文并翻译 | 示例
           

摘要

Based on screw theory, a novel improved inverse-kinematics approach for a type of six-DOF serial robot, "Qianjiang I", is proposed in this paper. The common kinematics model of the robot is based on the Denavit-Hartenberg (DH) notation method while its inverse kinematics has inefficient calculation and complicated solution, which cannot meet the demands of online real-time application. To solve this problem, this paper presents a new method to improve the efficiency of the inverse kinematics solution by introducing the screw theory. Unlike other methods, the proposed method only establishes two coordinates, namely the inertial coordinate and the tool coordinate; the screw motion of each link is carried out based on the inertial coordinate, ensuring definite geometric meaning. Furthermore, we adopt a new inverse kinematics algorithm, developing an improved sub-problem method along with Paden-Kahan sub-problems. This method has high efficiency and can be applied in real-time industrial operation. It is convenient to select the desired solutions directly from among multiple solutions by examining clear geometric meaning. Finally, the effectiveness and reliability performance of the new algorithm are analysed and verified in comparative experiments carried out on the six-DOF serial robot "Qianjiang I".
机译:基于螺丝理论,本文提出了一种新颖的改进了一种六-TOF串行机器人“Qianjiang I”的逆运动学方法。机器人的常见运动学模型基于Denavit-Hartenberg(DH)符号方法,而其逆运动学具有低效的计算和复杂解决方案,其无法满足在线实时应用的需求。为了解决这个问题,本文提出了一种通过引入螺杆理论来提高逆运动学解决方案效率的新方法。与其他方法不同,所提出的方法仅建立两个坐标,即惯性坐标和工具坐标;基于惯性坐标进行每个链路的螺钉运动,确保确定的几何含义。此外,我们采用了一种新的逆运动学算法,伴随着Paden-Kahan子问题的改进的子问题方法。该方法具有高效率,可应用于实时工业操作。通过检查清晰的几何含义,直接从多种解决方案中直接从多个解决方案中选择所需的解决方案是方便的。最后,分析了新算法的有效性和可靠性性能并验证了在六自由度串行机器人“Qianjiang I”的比较实验中进行了验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号