Hiparco Lins Vieira

Universidade de São Paulo

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Maíra Martins da Silva

Universidade de São Paulo

João Vitor de Carvalho Fontes

Universidade Federal de São Carlos

André T. Beck

Universidade de São Paulo

A.A.A. Menezes

Clemson University

Valdir Grassi

Universidade de São Paulo

ÍP

ÍTALO PELIÇÃO CALIARI

Universidade Federal de Viçosa

ÉW

Éric Wajnberg

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Cooperative Institutions

Universidade de São Paulo

Universidade Federal de São Carlos

Universidade Brasil

Clemson University

National Institute of Oceanography

Council of Scientific and Industrial Research

Sesame Workshop

University of Pennsylvania

Universidade Federal do Pará

Brazilian Center for Research in Energy and Materials

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Reliable and Failure-Free Workspaces for Motion Planning Algorithms for Parallel Manipulators Under Geometrical Uncertainties

Journal of Computational and Nonlinear Dynamics (2018)

Hiparco Lins Vieira João Vitor de Carvalho Fontes André T. Beck Maíra Martins da Silva

Manufacturing tolerances and other uncertainties may play an important role in the performance of parallel manipulators since they can affect the distance to a singular configuration. Motion planning strategies for parallel manipulators under uncertainty require decision making approaches for classifying reliable regions within the workspace. In this paper, we address fail free and reliable motion planning for parallel manipulators. Failure is related to parallel kinematic singularities in the motion equations or to ill-conditioning of the Jacobian matrices. Monte Carlo algorithm is employed to compute failure probabilities for a dense grid of manipulator workspace configurations. The inverse condition number of the Jacobian matrix is used to compute the distance between each configuration and a singularity. For supporting motion planning strategies, not only failure maps are constructed but also reliable and failure-free workspaces are obtained. On the one hand, the reliable workspace is obtained by minimizing the failure probabilities subject to a minimal workspace area. Differently, a failure-free workspace is found by maximizing the workspace area subject to a probability of failure equal to zero. A 3RRR manipulator is used as a case study. For this case study, the usage of the reliable strategy can be useful for robustifying motion planning algorithm without a significant reduction of the reliable regions within the workspace.

Work space

10.1115/1.4042015

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Citations (7)

Robust Critical Inverse Condition Number for a 3RRR Robot Using Failure Maps

Mechanisms and machine science (2017)

Hiparco Lins Vieira João Vitor de Carvalho Fontes André T. Beck Maíra Martins da Silva

Revolute joint

Work space

Robustness

Robot end effector

10.1007/978-3-319-67567-1_27

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Citations (8)

Improving RRT's Efficiency through Motion Primitives Generation Optimization

Hiparco Lins Vieira Valdir Grassi

Rapidly-exploring Random Tree (RRT) algorithm has been used for motion planning in numerous and diverse robotic applications. For applications which demands higher motion resolution, the computational cost increases together with the number of motion primitives used to expand the RRT. In this paper we present a method based on optimization by elimination which is applied to the Rapidly-exploring Random Tree algorithm to reduce its computational cost. This method optimizes the efficiency of motion primitives generation. It identifies tree expansion in promising areas by initially generating and analyzing only few motion primitives. Then it increases the number of primitives for motion resolution enhancement in those promising areas. The results achieved by applying this method evidence a substantial decrease in the computational cost.

Tree (set theory)

Random tree

10.1109/sbr.lars.robocontrol.2014.20

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Citations (3)

FAILURE MAPS FOR A KINEMATICALLY REDUNDANT PLANAR PARALLEL MANIPULATOR UNDER GEOMETRICAL UNCERTAINTIES

Maíra Martins da Silva Hiparco Lins Vieira

Manipulator (device)

10.26678/abcm.cobem2019.cob2019-0149

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Citations (0)

Redução do custo computacional do algoritmo RRT através de otimização por eliminação