To determine a collision free path for a robot between start and goal positions in an environment filled with obstacles is a very challenging task in the design of an autonomous robot path planning. This paper aims to select an optimal path planning algorithm for a mobile robot in structured environment. To achieve the goal, comprehensive strengths and weaknesses of different path planning algorithm are discussed and evaluated. A wooden box with some fixed obstacles and robot inside it is basically the environment. Information about the environment is used to build a roadmap or graph of the environment. After getting a convenient representation of the environment, then graph search methods can be used to obtain shortest possible path through this roadmap. It is well known that computing shortest paths for autonomous robots is an important task in many path planning applications. Selecting a suitable algorithm from the various algorithms reported in the literature is a decisive step in many applications including path planning task. A set of three shortest path algorithms that compute optimal path from start to goal location has been identified and these are Uniform Cost Search, Greedy Search and A* algorithm. After comparing execution time and path length of path computed by these three algorithms, A * algorithm proves to be best suited for this particular application of path planning.