Selection of manipulator system for multiple-goal task by evaluating task completion time and cost with computational time constraints
| Autor: | Tamio Arai, Jun Ota, Ryosuke Chiba, Tsuyoshi Ueyama, Yanjiang Huang, Lounell B. Gueta |
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| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
Page layout Computer science Particle swarm optimization computer.software_genre Computer Science Applications Task (project management) Human-Computer Interaction Set (abstract data type) Hardware and Architecture Control and Systems Engineering Convergence (routing) Motion planning computer Software Configuration design Selection (genetic algorithm) |
| Zdroj: | Advanced Robotics. 27:233-245 |
| ISSN: | 1568-5535 0169-1864 |
| DOI: | 10.1080/01691864.2013.755244 |
| Popis: | The focus of this study is on the problem of manipulator system selection for a multiple-goal task by evaluating task completion time and cost with computational time constraints. An approach integrating system selection, structural configuration design, layout design, motion planning, and relative cost calculation is proposed to solve this problem within a reasonable computational time. In the proposed approach, multiple-objective particle swarm optimization (MOPSO) is utilized to search for the appropriate manipulator system with appropriate structural configuration from a set of candidate systems. Particle swarm optimization (PSO) and the nearest neighborhood algorithm are employed in layout design and motion planning due to their high convergence speed. Three methods involving a random search algorithm are compared to the proposed approach through a simulation. The simulation is done with a set of tasks and the result shows the effectiveness of the proposed approach. |
| Databáze: | OpenAIRE |
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