| Summary: | 碩士 === 國立彰化師範大學 === 工業教育與技術學系 === 102 === The purpose of this study focuses on the optimal design of the shortest path programming and multi-point minimum position error of five-axis robot. The first stage, multi-group ant colony algorithm was applied to calculate the shortest path with many different path points, and program the priority moving order of it. The second stage, the minimum position error from point to point was calculated by using hybrid quantum particle swarm algorithm according to. In this study, the points of the fifteen random space positions were constructed first to be considered as the target of path programming. And used the operation which motor spins when five-axis robot moved to separate point according to the design parameters of the position error for further forecasting the optimal combination of parameters
Multi-group ant colony algorithm was used in this study to forecast the shortest path programming. To avoid trapping into the local solution in the process of calculation, a hybrid quantum particle swarm algorithm with mutation operator was performed to determine the feasible solution of minimum position error.
The results of simulation analysis showed that the path programming and position error can be improved. The shortest path programming can be reduced by twenty-four percentage to twenty-nine percentage; and the error of minimum position can be reduced by five to seven-bits after the decimal point.
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