{"title":"Singularity-Robust Inverse Kinematics for Serial Manipulators","authors":"I. Dulęba","doi":"10.14313/jamris/3-2023/21","DOIUrl":null,"url":null,"abstract":"This paper is a practical~guideline how to analyze and evaluate literature algorithms of singularity-robust inverse kinematics or to construct new ones. Additive, multiplicative and based on the Singularity ValueDecomposition (SVD) methods are examined to retrieve well conditioning of a matrix to be inverted in the Newton algorithm of inverse kinematics. It is shown that singularity avoidance can be performedin two different, but equivalent, ways: either via properly modified manipulability matrix or not allowing to decreese the minimal singular value below a given threshold. It is discussed which method can always be used and which only when some pre-conditions are met. Selected methods are compared to with respect to the efficiency of coping with singularities based on a theoretical analysis as well as simulation results. Also some questions important for mathematically and/or practically oriented roboticians are stated and answered.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"20 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Automation, Mobile Robotics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14313/jamris/3-2023/21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
This paper is a practical~guideline how to analyze and evaluate literature algorithms of singularity-robust inverse kinematics or to construct new ones. Additive, multiplicative and based on the Singularity ValueDecomposition (SVD) methods are examined to retrieve well conditioning of a matrix to be inverted in the Newton algorithm of inverse kinematics. It is shown that singularity avoidance can be performedin two different, but equivalent, ways: either via properly modified manipulability matrix or not allowing to decreese the minimal singular value below a given threshold. It is discussed which method can always be used and which only when some pre-conditions are met. Selected methods are compared to with respect to the efficiency of coping with singularities based on a theoretical analysis as well as simulation results. Also some questions important for mathematically and/or practically oriented roboticians are stated and answered.
期刊介绍:
Fundamentals of automation and robotics Applied automatics Mobile robots control Distributed systems Navigation Mechatronics systems in robotics Sensors and actuators Data transmission Biomechatronics Mobile computing