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Kinematic design of optimally fault tolerant robots for different joint failure probabilities

Producción científica: Article › revisión exhaustiva

10 Citas (Scopus)

Resumen

A measure of fault tolerance for different joint failure probabilities is defined based on the properties of the singular values of the Jacobian after failures. Using this measure, methods to design optimally fault tolerant robots for an arbitrary set of joint failure probabilities and multiple cases of joint failure probabilities are introduced separately. Given an arbitrary set of joint failure probabilities, the optimal null space that optimizes the fault tolerant measure is derived, and the associated isotropic Jacobians are constructed. The kinematic parameters of the optimally fault tolerant robots are then generated from these Jacobians. One special case, i.e., how to construct the optimal Jacobian of spatial 7R robots for both positioning and orienting is further discussed. For multiple cases of joint failure probabilities, the optimal robot is designed through optimizing the sum of the fault tolerant measures for all the possible joint failure probabilities. This technique is illustrated on planar 3R robots, and it is shown that there exists a family of optimal robots.

Idioma originalEnglish
Páginas (desde-hasta)827-834
Número de páginas8
PublicaciónIEEE Robotics and Automation Letters
Volumen3
N.º2
DOI
EstadoPublished - abr 2018

Nota bibliográfica

Publisher Copyright:
© 2017 IEEE.

Financiación

Manuscript received September 10, 2017; accepted December 31, 2017. Date of publication January 12, 2018; date of current version January 25, 2018. This letter was recommended for publication by Associate Editor A. Dietrich and Editor P. Rocco upon evaluation of the reviewers’ comments. This work was supported in part by the National Science Foundation under Contract IIS-0812437. (Corresponding author: Biyun Xie.) The author are with the Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523 USA (e-mail: biyunxie@ rams.colostate.edu; [email protected]). Digital Object Identifier 10.1109/LRA.2018.2792691

FinanciadoresNúmero del financiador
National Science Foundation (NSF)IIS-0812437

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Biomedical Engineering
    • Human-Computer Interaction
    • Mechanical Engineering
    • Computer Vision and Pattern Recognition
    • Computer Science Applications
    • Control and Optimization
    • Artificial Intelligence

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