The following paper presents how several navigation algorithms, methodologies and the tests' results, using three global (Voronoi diagrams, occupation maps, visibility graphs) and three local (neural network, fuzzy logic, potential fields) techniques, for a Lego NXT mobile robot to arrive to a settled goal were developed. Analyzing the techniques' pros and cons concerning to events the robot may face, and how the structures' own features stablish parameters for the robot reaching its goal are detailed. Next, every technique's algorithm and the field conditions such as obstacle evasion and next space available are described. Elements such as used amount of time, movement efficacy and the robot's reaction speed were chosen as the results' main criteria, due to the performance and efficiency rates of each technique. After evaluation, the advantages each technique has compared to the others will be shown in a table. Finally, the obtained solutions are put to test in hypothetical events in order to demonstrate how every technique can be applied; concluding that determining which technique to use depends mainly on the test conditions and the amount of environment data available.