在工業4.0製造流程革新的浪潮下，加上近年人力成本日益上升，多軸工業機械手臂因具有高自由度的特性，在各領域皆可見其應用。運動規劃為影機械手臂工作效率的重要因素，完善的運動規劃能使機械手臂在滿足各物理限制下，在最短時間內完成任務。而S-curve因具有連續性的優點，為運動規劃技術中常見的架構之一，本論文以對稱型S-curve為基礎，推導非對稱7段型S-curve，以提升運動規劃之彈性。針對工作空間上的運動規劃，雖可指定機械手臂既定的運動路徑，然而因其工作空間與軸關節空間兩者之間為非線性關係，有可能發生軸飽和的現象，即超過軸關節的物理限制。因此本論文基於非對稱7段型S-curve的架構，利用演化式演算法，求得在工作空間與軸關節空間的物理限制下達到時間最佳化之運動規劃。最後，利用電腦模擬與六軸機械手臂實機驗證本論文所提方法之可行性。

Riding the wave of the Industry 4.0 manufacturing process revolution and facing the prospect of ever-increasing labor costs, multi-axis industrial manipulators are now widely used in various fields due to their high degree of freedom. Motion planning is an important factor affecting the efficiency of industrial manipulators. Perfect motion planning enables the industrial manipulators to complete the task in the shortest time while satisfying physical constraints. S-curve is one of the most commonly used algorithms in motion planning due to its advantages in continuity. Therefore, based on the symmetrical S-curve, this thesis derives an asymmetric 7-segment S-curve to enhance the flexibility of motion planning. If motion planning is performed in the workspace, the moving path of the industrial manipulator can be specified. However, because of the nonlinear relationship between the workspace and the joint space, the phenomenon of joint saturation may occur. Namely, joint constraints may be violated. To cope with the aforementioned problem, this thesis proposes an approach that exploits evolutionary algorithms and asymmetric 7-segment S-curves to obtain time-optimized motion planning without violating the physical constraints of the workspace and joint space. The results of simulations and experiments conducted on a 6-DOF industrial manipulator indicate that the proposed approach is feasible.

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