MB-RRT: An Inverse Kinematics Solver of Reduced Dimension

The evolution of manipulator robots has increased the complexity of their models and applications, requiring that the inverse kinematics (IK) methods integrated into their control systems to have features such as fast convergence, completeness, low computational cost, and the ability to avoid local...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Matheus C. Santos, Lucas Molina, Elyson A. N. Carvalho, Eduardo O. Freire, Jose G. N. Carvalho, Phillipe C. Santos
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Inverse kinematics manipulators robots RRT Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/3784e9e8edb64ed98b11fd7c02c69ad2
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3784e9e8edb64ed98b11fd7c02c69ad2
record_format	dspace
spelling	oai:doaj.org-article:3784e9e8edb64ed98b11fd7c02c69ad22021-11-18T00:11:15ZMB-RRT: An Inverse Kinematics Solver of Reduced Dimension2169-353610.1109/ACCESS.2021.3123645https://doaj.org/article/3784e9e8edb64ed98b11fd7c02c69ad22021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9591603/https://doaj.org/toc/2169-3536The evolution of manipulator robots has increased the complexity of their models and applications, requiring that the inverse kinematics (IK) methods integrated into their control systems to have features such as fast convergence, completeness, low computational cost, and the ability to avoid local minima and singularities. We propose in this paper a new probabilistic IK solver based on the probabilistic search method known as Rapidly-Exploring Random Tree (RRT), the Workspace-RRT. The technique grows the tree as a spatial representation of the manipulator on the workspace instead of the configuration space, which reduces the search space up to 3 dimensions. Based on this new representation we also present the Manipulator-Based Rapidly Random Tree (MB-RRT) by incorporating to the Workspace-RRT a new probability model and a new metric for the closest node. We evaluate the presented methods through simulated experiments in the Matlab software. First, we evaluate the impact of the proposed aspects through a comparison between the RRT-based IK solvers, which emphasizes the proposed changes as a key to make the method suitable for the IK problem. At last, we show the use of the MB-RRT for precision tasks and obstructed environments.Matheus C. SantosLucas MolinaElyson A. N. CarvalhoEduardo O. FreireJose G. N. CarvalhoPhillipe C. SantosIEEEarticleInverse kinematicsmanipulatorsrobotsRRTElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 148558-148573 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Inverse kinematics manipulators robots RRT Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Inverse kinematics manipulators robots RRT Electrical engineering. Electronics. Nuclear engineering TK1-9971 Matheus C. Santos Lucas Molina Elyson A. N. Carvalho Eduardo O. Freire Jose G. N. Carvalho Phillipe C. Santos MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
description	The evolution of manipulator robots has increased the complexity of their models and applications, requiring that the inverse kinematics (IK) methods integrated into their control systems to have features such as fast convergence, completeness, low computational cost, and the ability to avoid local minima and singularities. We propose in this paper a new probabilistic IK solver based on the probabilistic search method known as Rapidly-Exploring Random Tree (RRT), the Workspace-RRT. The technique grows the tree as a spatial representation of the manipulator on the workspace instead of the configuration space, which reduces the search space up to 3 dimensions. Based on this new representation we also present the Manipulator-Based Rapidly Random Tree (MB-RRT) by incorporating to the Workspace-RRT a new probability model and a new metric for the closest node. We evaluate the presented methods through simulated experiments in the Matlab software. First, we evaluate the impact of the proposed aspects through a comparison between the RRT-based IK solvers, which emphasizes the proposed changes as a key to make the method suitable for the IK problem. At last, we show the use of the MB-RRT for precision tasks and obstructed environments.
format	article
author	Matheus C. Santos Lucas Molina Elyson A. N. Carvalho Eduardo O. Freire Jose G. N. Carvalho Phillipe C. Santos
author_facet	Matheus C. Santos Lucas Molina Elyson A. N. Carvalho Eduardo O. Freire Jose G. N. Carvalho Phillipe C. Santos
author_sort	Matheus C. Santos
title	MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
title_short	MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
title_full	MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
title_fullStr	MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
title_full_unstemmed	MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
title_sort	mb-rrt: an inverse kinematics solver of reduced dimension
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/3784e9e8edb64ed98b11fd7c02c69ad2
work_keys_str_mv	AT matheuscsantos mbrrtaninversekinematicssolverofreduceddimension AT lucasmolina mbrrtaninversekinematicssolverofreduceddimension AT elysonancarvalho mbrrtaninversekinematicssolverofreduceddimension AT eduardoofreire mbrrtaninversekinematicssolverofreduceddimension AT josegncarvalho mbrrtaninversekinematicssolverofreduceddimension AT phillipecsantos mbrrtaninversekinematicssolverofreduceddimension
_version_	1718425155261169664

MB-RRT: An Inverse Kinematics Solver of Reduced Dimension

Ejemplares similares