Autonomous mobile robots face many challenges, and path planning is one of the first to be solved. To solve path planning, many solutions have been proposed, being the deterministic methods the ones that produced the best results. One of the these methods inspired by the concept of Potential Fields is the Fast Marching Method. This method belongs to a family of methods that solve the Eikonal equation, called Fast Methods. However, the only method applied to solve path planning is Fast Marching Method, then we propose to use the Fast Iterative Method instead due its scalability feature. Also we proposed an improvement to Fast Iterative Method called Fast Iterative Method Square, this comes from the need to have methods that generates safe paths. This proposal seeks to demostrate that the Fast Iterative Method and Fast Iterative Method Square are applicable to solve path planning and that they also present a better performance than the Fast Marching Method in all the comparisons made. In addition, Fast Iterative Method allows us to handle maps of large dimensions due to its highly parallel feature.