Cargando…

A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning

When a manipulator works in dynamic environments, it may be affected by obstacles and may cause danger to people around. This requires the manipulator to be able to plan the obstacle avoidance motion in real time. Therefore, the problem solved in this paper is dynamic obstacle avoidance with the who...

Descripción completa

Detalles Bibliográficos
Autores principales: Ju, Fengjia, Jin, Hongzhe, Wang, Binluan, Zhao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224202/
https://www.ncbi.nlm.nih.gov/pubmed/37430556
http://dx.doi.org/10.3390/s23104642
_version_ 1785050120886157312
author Ju, Fengjia
Jin, Hongzhe
Wang, Binluan
Zhao, Jie
author_facet Ju, Fengjia
Jin, Hongzhe
Wang, Binluan
Zhao, Jie
author_sort Ju, Fengjia
collection PubMed
description When a manipulator works in dynamic environments, it may be affected by obstacles and may cause danger to people around. This requires the manipulator to be able to plan the obstacle avoidance motion in real time. Therefore, the problem solved in this paper is dynamic obstacle avoidance with the whole body of the redundant manipulator. The difficulty of this problem is how to model the manipulator to reflect the motion relationship between the manipulator and the obstacle. In order to describe accurately the occurrence conditions of the collision, we propose the triangular collision plane, a predictable obstacle avoidance model based on the geometric configuration of the manipulator. Based on this model, three cost functions, including the cost of the motion state, the cost of a head-on collision, and the cost of the approach time, are established and regarded as optimization objectives in the inverse kinematics solution of the redundant manipulator combined with the gradient projection method. The simulations and experiments on the redundant manipulator and the comparison with the distance-based obstacle avoidance point method show that our method improves the response speed of the manipulator and the safety of the system.
format Online
Article
Text
id pubmed-10224202
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-102242022023-05-28 A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning Ju, Fengjia Jin, Hongzhe Wang, Binluan Zhao, Jie Sensors (Basel) Article When a manipulator works in dynamic environments, it may be affected by obstacles and may cause danger to people around. This requires the manipulator to be able to plan the obstacle avoidance motion in real time. Therefore, the problem solved in this paper is dynamic obstacle avoidance with the whole body of the redundant manipulator. The difficulty of this problem is how to model the manipulator to reflect the motion relationship between the manipulator and the obstacle. In order to describe accurately the occurrence conditions of the collision, we propose the triangular collision plane, a predictable obstacle avoidance model based on the geometric configuration of the manipulator. Based on this model, three cost functions, including the cost of the motion state, the cost of a head-on collision, and the cost of the approach time, are established and regarded as optimization objectives in the inverse kinematics solution of the redundant manipulator combined with the gradient projection method. The simulations and experiments on the redundant manipulator and the comparison with the distance-based obstacle avoidance point method show that our method improves the response speed of the manipulator and the safety of the system. MDPI 2023-05-10 /pmc/articles/PMC10224202/ /pubmed/37430556 http://dx.doi.org/10.3390/s23104642 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ju, Fengjia
Jin, Hongzhe
Wang, Binluan
Zhao, Jie
A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title_full A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title_fullStr A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title_full_unstemmed A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title_short A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
title_sort predictable obstacle avoidance model based on geometric configuration of redundant manipulators for motion planning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224202/
https://www.ncbi.nlm.nih.gov/pubmed/37430556
http://dx.doi.org/10.3390/s23104642
work_keys_str_mv AT jufengjia apredictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT jinhongzhe apredictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT wangbinluan apredictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT zhaojie apredictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT jufengjia predictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT jinhongzhe predictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT wangbinluan predictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning
AT zhaojie predictableobstacleavoidancemodelbasedongeometricconfigurationofredundantmanipulatorsformotionplanning