<![CDATA[In the robot environment with static obstacles, robots designed to avoid obstacles and move from the initial position to the destination position, the consumption of the minimum value and the search for the shortest path as the current research, most of the studies are based on obstacle detection to search for more than one path planning. The path using path planning has two sampling methods based on which by working according to random nodes while searching based on using heuristics to find the path. Fast-RRT*-A* were to optimize a path with fast time intensity. From Fast-RRT* developed with improvement-RRT with optimal fast, namely fast optimal in an unreachable space from random trees introduced for speed and algorithm stability; (2) Random steering is used in expansion to solve performance problems in tight spaces; (3) Path fusion path adjustments are obtained quickly. The results of this study are in the form of a profit map comparing the three PRC algorithms* with a time of 48.6474, A* with a time of 38.7527, and FastRRT*-A* with a time of 10.1411, So these three steps make Fast- RRT*-A*.]]>
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