we present an algorithm for path planning to a target for mobile robot in unknown environment. The proposed algorithm allows a mobile robot to navigate through static obstacles, and finding the path in order to reach the target without collision. This algorithm provides the robot the possibility to move from the initial position to the final position (target). The proposed path finding strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. The robot moves within the unknown environment by sensing and avoiding the obstacles coming across its way towards the target. When the mission is executed, it is necessary to plan an optimal or feasible path for itself avoiding obstructions in its way and minimizing a cost such as time, energy, and distance. In order to get an intelligent component, the use of Fuzzy Logic In order to get an intelligent component, the use of Fuzzy Logic (FL), and Expert Systems (ES) is necessary to bring the behavior of Intelligent Autonomous Vehicles (IAV). To present a real intelligent task and to deal with autonomy requirements such as power and thermal, (FL), and Expert Systems (ES) is necessary to bring the behavior of Intelligent Autonomous Vehicles (IAV). The aim work must make the robot able to achieve these tasks: to avoid obstacles, and to make ones way toward its target by ES_FL system capturing the behavior of a human expert. The integration of ES and FL has proven to be a way to develop useful real-world applications, and hybrid systems involving robust adaptive control. The proposed approach has the advantage of being generic and can be changed at the user demand. The results are satisfactory to see the great number of environments treated. The results are satisfactory and promising.