Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. GA is utilized to calculate the near-optimal task scheduling for the two robots. On top of that, the EM is recommended as a suitabl...
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my.uniten.dspace-299482023-12-29T15:43:43Z Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators Abed I.A. Sahari K.S.M. Koh S.P. Tiong S.K. Jagadeesh P. 55568292900 57218170038 22951210700 15128307800 11340187300 Dual robots Electromagnetism-like algorithm Genetic algorithm Task scheduling Electromagnetism Industrial robots Manipulators Multitasking Optimization Robot applications Scheduling algorithms Dual manipulators Dual robots Electromagnetism-like algorithm Multiple solutions Point to point Static obstacles Task-scheduling Visual Basic .NET Genetic algorithms A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. GA is utilized to calculate the near-optimal task scheduling for the two robots. On top of that, the EM is recommended as a suitable alternative to obtain multiple solutions at each task points for both manipulators with less error. During the course of the tour, the dual robots move from point to point with less cycle time, while ensuring that no collision occurs between the two manipulators or between the dual manipulators and the static obstacles in the workspace. The movement and the configurations of the manipulators at the task points were visualized using a simulator developed via Visual Basic. Net. The method is verified using two simulators acting as examples for two identical four-link planar robots working in the environment, with square-shaped obstacles cluttered at different locations. � 2013 IEEE. Final 2023-12-29T07:43:43Z 2023-12-29T07:43:43Z 2013 Conference paper 10.1109/R10-HTC.2013.6669038 2-s2.0-84893406143 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893406143&doi=10.1109%2fR10-HTC.2013.6669038&partnerID=40&md5=22160f620f8924f1feedbbaf1fa715f3 https://irepository.uniten.edu.my/handle/123456789/29948 6669038 182 187 Scopus |
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Dual robots Electromagnetism-like algorithm Genetic algorithm Task scheduling Electromagnetism Industrial robots Manipulators Multitasking Optimization Robot applications Scheduling algorithms Dual manipulators Dual robots Electromagnetism-like algorithm Multiple solutions Point to point Static obstacles Task-scheduling Visual Basic .NET Genetic algorithms |
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Dual robots Electromagnetism-like algorithm Genetic algorithm Task scheduling Electromagnetism Industrial robots Manipulators Multitasking Optimization Robot applications Scheduling algorithms Dual manipulators Dual robots Electromagnetism-like algorithm Multiple solutions Point to point Static obstacles Task-scheduling Visual Basic .NET Genetic algorithms Abed I.A. Sahari K.S.M. Koh S.P. Tiong S.K. Jagadeesh P. Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
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A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. GA is utilized to calculate the near-optimal task scheduling for the two robots. On top of that, the EM is recommended as a suitable alternative to obtain multiple solutions at each task points for both manipulators with less error. During the course of the tour, the dual robots move from point to point with less cycle time, while ensuring that no collision occurs between the two manipulators or between the dual manipulators and the static obstacles in the workspace. The movement and the configurations of the manipulators at the task points were visualized using a simulator developed via Visual Basic. Net. The method is verified using two simulators acting as examples for two identical four-link planar robots working in the environment, with square-shaped obstacles cluttered at different locations. � 2013 IEEE. |
| author2 |
55568292900 |
| author_facet |
55568292900 Abed I.A. Sahari K.S.M. Koh S.P. Tiong S.K. Jagadeesh P. |
| format |
Conference paper |
| author |
Abed I.A. Sahari K.S.M. Koh S.P. Tiong S.K. Jagadeesh P. |
| author_sort |
Abed I.A. |
| title |
Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| title_short |
Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| title_full |
Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| title_fullStr |
Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| title_full_unstemmed |
Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| title_sort |
using electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators |
| publishDate |
2023 |
| _version_ |
1806426257518231552 |
| score |
13.222552 |