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Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints

Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the ma...

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Detalles Bibliográficos
Autores principales: Wang, Peng, Ma, Hongwei, Zhang, Ye, Cao, Xiangang, Wu, Xudong, Wei, Xiaorong, Zhou, Wenjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181549/
https://www.ncbi.nlm.nih.gov/pubmed/37177621
http://dx.doi.org/10.3390/s23094412
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author Wang, Peng
Ma, Hongwei
Zhang, Ye
Cao, Xiangang
Wu, Xudong
Wei, Xiaorong
Zhou, Wenjian
author_facet Wang, Peng
Ma, Hongwei
Zhang, Ye
Cao, Xiangang
Wu, Xudong
Wei, Xiaorong
Zhou, Wenjian
author_sort Wang, Peng
collection PubMed
description Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the manipulator and the target when the manipulator grabs the target. In this method, the mathematical model of seven-segment manipulator trajectory planning is constructed first. The mathematical model of synchronous tracking of dynamic targets based on a time-minimum manipulator is constructed by taking the robot’s acceleration, speed, and synchronization as constraints. The model transforms the multi-constraint-solving problem into a single-objective-solving problem. Finally, the particle swarm optimization algorithm is used to solve the model. The calculation results are put into the trajectory planning model of the manipulator to obtain the synchronous tracking trajectory of the manipulator. Simulation and experiments show that each joint of the robot’s arm can synchronously track dynamic targets within the constraint range. This method can ensure the synchronization of the position, speed, and acceleration of the moving target and the target after tracking. The average position error is 2.1 mm, and the average speed error is 7.4 mm/s. The robot has a high tracking accuracy, which further improves the robot’s grasping stability and success rate.
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spelling pubmed-101815492023-05-13 Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints Wang, Peng Ma, Hongwei Zhang, Ye Cao, Xiangang Wu, Xudong Wei, Xiaorong Zhou, Wenjian Sensors (Basel) Article Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the manipulator and the target when the manipulator grabs the target. In this method, the mathematical model of seven-segment manipulator trajectory planning is constructed first. The mathematical model of synchronous tracking of dynamic targets based on a time-minimum manipulator is constructed by taking the robot’s acceleration, speed, and synchronization as constraints. The model transforms the multi-constraint-solving problem into a single-objective-solving problem. Finally, the particle swarm optimization algorithm is used to solve the model. The calculation results are put into the trajectory planning model of the manipulator to obtain the synchronous tracking trajectory of the manipulator. Simulation and experiments show that each joint of the robot’s arm can synchronously track dynamic targets within the constraint range. This method can ensure the synchronization of the position, speed, and acceleration of the moving target and the target after tracking. The average position error is 2.1 mm, and the average speed error is 7.4 mm/s. The robot has a high tracking accuracy, which further improves the robot’s grasping stability and success rate. MDPI 2023-04-30 /pmc/articles/PMC10181549/ /pubmed/37177621 http://dx.doi.org/10.3390/s23094412 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
Wang, Peng
Ma, Hongwei
Zhang, Ye
Cao, Xiangang
Wu, Xudong
Wei, Xiaorong
Zhou, Wenjian
Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title_full Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title_fullStr Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title_full_unstemmed Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title_short Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
title_sort trajectory planning for coal gangue sorting robot tracking fast-mass target under multiple constraints
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181549/
https://www.ncbi.nlm.nih.gov/pubmed/37177621
http://dx.doi.org/10.3390/s23094412
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