A Forward Kinematics Data Structure for Efficient Evolutionary Inverse Kinematics

被引：1

作者：

Starke, Sebastian ^{[1
]}

Hendrich, Norman ^{[1
]}

Zhang, Jianwei ^{[1
]}

机构：

[1] Univ Hamburg, Dept Informat, Grp TAMS Tech Aspects Multimodal Syst, D-22527 Hamburg, Germany

来源：

COMPUTATIONAL KINEMATICS | 2018年 / 50卷

基金：

美国国家科学基金会;

关键词：

Forward kinematics; Inverse kinematics; Data structures; Computational efficiency; Evolutionary optimisation; Robotics; Character animation;

D O I：

10.1007/978-3-319-60867-9_64

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Various approaches to solving inverse kinematics implicitly rely on computing forward kinematics in order to obtain an approximate solution. This work proposes an optimised data structure to efficiently compute these equations by avoiding redundant transformations and calculations. This is particulary relevant for highly articulated kinematic models and multiple end effectors with shared joints along their kinematic chains. By integrating the developed OFKT (Optimised Forward Kinematics Tree), less computation time within each iteration is required, which contributes to a significant speedup in convergence. Experiments were conducted using a novel evolutionary approach which was designed for handling complex kinematic geometries.

引用

页码：560 / 568

页数：9