Autonomous robotics is one of the key subjects of this generation of research and has grown to be more and more popular in recent years, especially in such industries, hospitals, hotels, and plenty more. Path planning is a critical issue in the applications of these autonomous mobile robots. This means the path planning task is to find a collision-free path for the robot, in an indoor environment that has cluttered obstacles, from the specified beginning or start point to the end or desired goal destination while satisfying certain optimization criteria. This paper explores the optimization of path planning of autonomous mobile robots in indoor environments using A star algorithm methods in different cluttered environments. The main contribution of this paper aimed to improve the path planning of autonomous mobile robots in the indoor environment on the basis of the A star algorithm and offer a unique capability field approach for time efficiency, moving the robots in the complex obstacle to getting the goal, and obtain better path for robots as well as for solving the problems that the traditional A* algorithm method often converges of much time, long distance, and some oscillatory movement of the robot. The simulation results show that the performance of the methods of path planning algorithm is getting good results which are applied in different environments and obtained better results on finding a short and safe path planning for the autonomous robot.
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