This paper presents an experimental study using two robots to investigate the effectiveness of different navigation strategies, including random, reactive, planning, and anticipation. The robots were tasked with shifting places with each other in various environments with or without obstacles. The results indicate that while anticipation can be advantageous, it is not always superior to purely reactive strategies. The study found that in environments with obstacles, reactive and planning strategies performed better than anticipation, as they avoided collisions and took more efficient paths. However, in simpler environments, anticipation showed potential by reducing the time difference between robots reaching their goals. The study also explored different methods of using anticipated behavior, such as fixed rank and higher rank for the robot closest to the goal, and found that these methods had varying degrees of success. Overall, the findings suggest that the effectiveness of anticipation depends on the complexity of the environment and the accuracy of the robot's control system.This paper presents an experimental study using two robots to investigate the effectiveness of different navigation strategies, including random, reactive, planning, and anticipation. The robots were tasked with shifting places with each other in various environments with or without obstacles. The results indicate that while anticipation can be advantageous, it is not always superior to purely reactive strategies. The study found that in environments with obstacles, reactive and planning strategies performed better than anticipation, as they avoided collisions and took more efficient paths. However, in simpler environments, anticipation showed potential by reducing the time difference between robots reaching their goals. The study also explored different methods of using anticipated behavior, such as fixed rank and higher rank for the robot closest to the goal, and found that these methods had varying degrees of success. Overall, the findings suggest that the effectiveness of anticipation depends on the complexity of the environment and the accuracy of the robot's control system.