Finding the best way for the robot to get from one place to another is a big part of robotics. Finding the best way to get from one place to another can be hard, especially when there are fixed hurdles in the way. In order to get to its goal without running into any problems, the A* algorithm is a well-known path planning method. For the robot to be diverted as little as possible, this thesis suggests the best way to choose a path in settings with static obstacles using the A* algorithm. As long as the robot stays on its original path and doesn’t run into any hurdles, the method should be able to find the best path. Create a cost function that takes into account both the quickest path and the robot’s departure from its original path as part of the suggested way. This is followed by using the A* method to find the best way that keeps the cost function as low as possible. Our proposed method worked well when we used it on a virtual robot base. With few deviations from its original path, the robot was able to move through the static obstacle surface. In terms of keeping the robot from getting distracted, the suggested way was also much better than the basic A* algorithm. The suggested way can finally be used to lead a robot through a room full of fixed obstacles while keeping it as close to the original plan as possible.