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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Reliable motion planning for parallel manipulators

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Author(s):
Vieira, Hiparco Lins [1] ; Wajnberg, Eric [2, 3] ; Beck, Andre Teofilo [1] ; da Silva, Maira Martins [1]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Engn Sch, Av Trab Sao Carlense 400, Parque Arnold Schimidt, Sao Carlos, SP - Brazil
[2] INRA, 400 Route Chappes, BP 167, F-06903 Sophia Antipolis - France
[3] INRIA, Projet Hephaistos, 2004 Route Lucioles, BP 93, F-06902 Sophia Antipolis - France
Total Affiliations: 3
Document type: Journal article
Source: MECHANISM AND MACHINE THEORY; v. 140, p. 553-566, OCT 2019.
Web of Science Citations: 1
Abstract

Geometric uncertainties may jeopardize the performance of parallel manipulators, especially during motion planning. Recent research demonstrated that, during motion planning and due to uncertainties, manipulators may accidentally assume low performance or singular configurations. Thus, reliable motion planning algorithms are required. Very few algorithms were proposed to avoid such problem in parallel manipulators. This paper presents a reliable motion planning technique. First, failure modes are defined. Then, a Monte Carlo simulation is used to provide information on how the manipulator's uncertainties affect its conditioning. Based on this simulation, probabilities of failure are computed for several manipulator workspace configurations. After that, an artificial neural network metamodel is trained to overcome Monte Carlo's computational inefficiency on the failure probability estimation. This metamodel is assessed by an iterative strategy that exploits genetic operators to compute optimal trajectories avoiding regions that are considerably affected by uncertainties. Due to its modular methodology, the technique can be easily adapted for different applications. A 3 (R) under bar RR manipulator is used as a case study. (C) 2019 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 18/21336-0 - Towards high speed parallel kinematic machines, Phase II: instrumentation, modeling and control of a flexible manipulator
Grantee:Maira Martins da Silva
Support Opportunities: Regular Research Grants
FAPESP's process: 14/01809-0 - Towards high speed planar robotic manipulators, Phase I: kinematic redundancy
Grantee:Maira Martins da Silva
Support Opportunities: Regular Research Grants