最佳化路徑規劃是移動機器人研究重要議題之一。它是指在擁有障礙物的空間環境下，搜尋出一條從起點至目標點的較佳運動路徑，讓移動機器人不能與障礙物有任何碰撞，使之能安全通過，且為最短路徑。而本研究採用粒子群演算法來設計，其具有下列優點，包括：參數調整容易，以公式為主體而沒有太多繁瑣的過程，且能夠有效率地獲得全域最佳解。

首先，設計三種不同尺寸的環境地圖，其中每種地圖皆含兩種不同地形變化。其次，再結合開放式車輛路徑問題來討論移動機器人路徑規劃。模擬結果顯示：即使地圖含有地形變化與路由條件，粒子群會隨著迭代而找到最佳路徑，亦即其可以找到具最短時間的最佳路徑。

Optimal path planning is one of the important issues in mobile robot study. It tries to find the shortest path from the start point to the end point for a mobile robot and to avoid the collision with obstacles at the same time. This study adopts the Particle Swarm Optimization (PSO) algorithm to design the optimal path planning. This algorithm less owns the benefits of easy adjustment for parameters, tedious process based on the formula, and being able to efficiently to obtain the optimal global solution.
First, we design three classes of maps with different sizes. Therein, each map has two terrain changes. Moreover, we incorporate the Vehicle Routing Problem (VRP) in mobile robot path planning. Simulation results indicate that the particle swarm will find the optimal path even under terrain changes and routing conditions, that is to say, it can find the optimal path with the minimum time cost.

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