DSpaceCRIS@UNITENThe DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.http://dspace.uniten.edu.my/jspui2019-07-20T15:51:44Z2019-07-20T15:51:44Z5041Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic AlgorithmAbed, I.A.Koh, S.P.Sahari, K.S.M.Jagadeesh, P.Tiong, S.K.http://dspace.uniten.edu.my/jspui/handle/123456789/66832018-01-03T01:52:13Z2014-01-01T00:00:00ZTitle: Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm
Authors: Abed, I.A.; Koh, S.P.; Sahari, K.S.M.; Jagadeesh, P.; Tiong, S.K.
Abstract: A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. A GA is utilized to calculate the near-optimal task scheduling for both robots, and the MEMTDLS is recommended as a suitable alternative in obtaining multiple solutions at each task point for both manipulators with minimal error. During the course of the tour, the robots move from point to point with a short cycle time, while ensuring that no collision occurs between the two manipulators themselves 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 illustrated using a simulator that was developed via Visual Basic.Net. The method is verified using two simulators that are used as examples for two identical four-link planar robots that work in the environment, with square-shaped obstacles cluttered at different locations. © 2014 King Fahd University of Petroleum and Minerals.
2014-01-01T00:00:00ZOptimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic AlgorithmAbed, I.A.Koh, S.P.Sahari, K.S.M.Jagadeesh, P.Tiong, S.K.http://dspace.uniten.edu.my/jspui/handle/123456789/69842018-01-11T08:27:44Z2014-01-01T00:00:00ZTitle: Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm
Authors: Abed, I.A.; Koh, S.P.; Sahari, K.S.M.; Jagadeesh, P.; Tiong, S.K.
Abstract: A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. A GA is utilized to calculate the near-optimal task scheduling for both robots, and the MEMTDLS is recommended as a suitable alternative in obtaining multiple solutions at each task point for both manipulators with minimal error. During the course of the tour, the robots move from point to point with a short cycle time, while ensuring that no collision occurs between the two manipulators themselves 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 illustrated using a simulator that was developed via Visual Basic.Net. The method is verified using two simulators that are used as examples for two identical four-link planar robots that work in the environment, with square-shaped obstacles cluttered at different locations. © 2014 King Fahd University of Petroleum and Minerals.
2014-01-01T00:00:00ZUsing Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulatorsAbed, I.A.Sahari, K.S.M.Koh, S.P.Tiong, S.K.Jagadeesh, P.http://dspace.uniten.edu.my/jspui/handle/123456789/69872018-01-11T08:27:45Z2013-01-01T00:00:00ZTitle: Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Authors: Abed, I.A.; Sahari, K.S.M.; Koh, S.P.; Tiong, S.K.; Jagadeesh, P.
Abstract: 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.
2013-01-01T00:00:00ZUsing Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulatorsAbed, I.A.Sahari, K.S.M.Koh, S.P.Tiong, S.K.Jagadeesh, P.http://dspace.uniten.edu.my/jspui/handle/123456789/66842018-01-03T02:03:40Z2013-01-01T00:00:00ZTitle: Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Authors: Abed, I.A.; Sahari, K.S.M.; Koh, S.P.; Tiong, S.K.; Jagadeesh, P.
Abstract: 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.
2013-01-01T00:00:00Z