基于Lie理论的串联机械臂雅可比矩阵及其高阶导数解析表达式*

Zhongtao Fu, Emmanouil Spyrakos-Papastavridis, Yen-hua Lin, J. Dai
{"title":"基于Lie理论的串联机械臂雅可比矩阵及其高阶导数解析表达式*","authors":"Zhongtao Fu, Emmanouil Spyrakos-Papastavridis, Yen-hua Lin, J. Dai","doi":"10.1109/ICRA40945.2020.9197131","DOIUrl":null,"url":null,"abstract":"Serial manipulator kinematics provide a mapping between joint variables in joint-space coordinates, and end-effector configurations in task-space Cartesian coordinates. Velocity mappings are represented via the manipulator Jacobian produced by direct differentiation of the forward kinematics. Acquisition of acceleration, jerk, and snap expressions, typically utilized for accurate trajectory-tracking, requires the computation of high-order Jacobian derivatives. As compared to conventional numerical/D-H approaches, this paper proposes a novel methodology to derive the Jacobians and their high-order derivatives symbolically, based on Lie theory, which requires that the derivatives are calculated with respect to each joint variable and time. Additionally, the technique described herein yields a mathematically sound solution to the high-order Jacobian derivatives, which distinguishes it from other relevant works. Performing computations with respect to the two inertial-fixed and body-fixed frames, the analytical form of the spatial and body Jacobians are derived, as well as their higher-order derivatives, without resorting to any approximations, whose expressions would depend explicitly on the joint state and the choice of reference frames. The proposed method provides more tractable computation of higher-order Jacobian derivatives, while its effectiveness has been verified by conducting a comparative analysis based on experimental data extracted from a KUKA LRB iiwa7 R800 manipulator.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"43 1","pages":"7095-7100"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Analytical Expressions of Serial Manipulator Jacobians and their High-Order Derivatives based on Lie Theory*\",\"authors\":\"Zhongtao Fu, Emmanouil Spyrakos-Papastavridis, Yen-hua Lin, J. Dai\",\"doi\":\"10.1109/ICRA40945.2020.9197131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Serial manipulator kinematics provide a mapping between joint variables in joint-space coordinates, and end-effector configurations in task-space Cartesian coordinates. Velocity mappings are represented via the manipulator Jacobian produced by direct differentiation of the forward kinematics. Acquisition of acceleration, jerk, and snap expressions, typically utilized for accurate trajectory-tracking, requires the computation of high-order Jacobian derivatives. As compared to conventional numerical/D-H approaches, this paper proposes a novel methodology to derive the Jacobians and their high-order derivatives symbolically, based on Lie theory, which requires that the derivatives are calculated with respect to each joint variable and time. Additionally, the technique described herein yields a mathematically sound solution to the high-order Jacobian derivatives, which distinguishes it from other relevant works. Performing computations with respect to the two inertial-fixed and body-fixed frames, the analytical form of the spatial and body Jacobians are derived, as well as their higher-order derivatives, without resorting to any approximations, whose expressions would depend explicitly on the joint state and the choice of reference frames. The proposed method provides more tractable computation of higher-order Jacobian derivatives, while its effectiveness has been verified by conducting a comparative analysis based on experimental data extracted from a KUKA LRB iiwa7 R800 manipulator.\",\"PeriodicalId\":6859,\"journal\":{\"name\":\"2020 IEEE International Conference on Robotics and Automation (ICRA)\",\"volume\":\"43 1\",\"pages\":\"7095-7100\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Robotics and Automation (ICRA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRA40945.2020.9197131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA40945.2020.9197131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

串联机械臂运动学提供了关节空间坐标中关节变量和任务空间笛卡尔坐标中末端执行器构型之间的映射。速度映射是通过对正运动学直接微分得到的机械臂雅可比矩阵来表示的。通常用于精确轨迹跟踪的加速度、震动和弹跳表达式的获取需要计算高阶雅可比导数。与传统的数值/D-H方法相比,本文提出了一种新的基于李氏理论的雅可比矩阵及其高阶导数的符号化推导方法,该方法要求对每个关节变量和时间进行导数计算。此外,本文所描述的技术产生了高阶雅可比导数的数学合理解,这与其他相关工作不同。对两个固定惯性和固定体坐标系进行计算,推导出空间雅可比矩阵和物体雅可比矩阵的解析形式,以及它们的高阶导数,而不使用任何近似,其表达式将明确地依赖于关节状态和参考坐标系的选择。基于KUKA LRB iiwa7 R800机械手的实验数据对比分析,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytical Expressions of Serial Manipulator Jacobians and their High-Order Derivatives based on Lie Theory*
Serial manipulator kinematics provide a mapping between joint variables in joint-space coordinates, and end-effector configurations in task-space Cartesian coordinates. Velocity mappings are represented via the manipulator Jacobian produced by direct differentiation of the forward kinematics. Acquisition of acceleration, jerk, and snap expressions, typically utilized for accurate trajectory-tracking, requires the computation of high-order Jacobian derivatives. As compared to conventional numerical/D-H approaches, this paper proposes a novel methodology to derive the Jacobians and their high-order derivatives symbolically, based on Lie theory, which requires that the derivatives are calculated with respect to each joint variable and time. Additionally, the technique described herein yields a mathematically sound solution to the high-order Jacobian derivatives, which distinguishes it from other relevant works. Performing computations with respect to the two inertial-fixed and body-fixed frames, the analytical form of the spatial and body Jacobians are derived, as well as their higher-order derivatives, without resorting to any approximations, whose expressions would depend explicitly on the joint state and the choice of reference frames. The proposed method provides more tractable computation of higher-order Jacobian derivatives, while its effectiveness has been verified by conducting a comparative analysis based on experimental data extracted from a KUKA LRB iiwa7 R800 manipulator.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信