# Formation Control of Multiple Autonomous Mobile Robots Using Turkish Natural Language Processing
## 5 Experimental Studies  
This section presents experimental studies on the formation control of multiple mobile robots using NLP and different scenarios envisioned for formation control. The Turkish NLP approach asks a group of mobile robots to follow a prescribed or desired trajectory under other conditions. In the simulation environment, obstacles were assumed to exist, and the mobile robots were asked to move. Considering these obstacles, the robots were given commands in Turkish and asked to do what was necessary. The general view of the environment with obstacles in which the robots move is shown in Figure 7. After calculating the coordinates of the target point, the A* algorithm is used to calculate the optimal/economic path.  
The terms \"In front of the target\" and \"behind the target\" in the Turkish commands given to the robot are shown in Figure 9, and the formulation is generated. Some preliminary assumptions were made, and experimental studies were carried out on the formation control of the mobile robot system using Turkish NLP. Instead of very complex Turkish sentences, sentence structures containing one or more commands were used. The functional status of the leader and follower robots in formation control was initially determined as leader, follower 1, follower 2, \(\ldots\) follower n. Multi-robot systems using the leader-follower control method have at least one leader, with the rest of the agents as followers. The control design is such that the followers monitor the leader's position and follow the leader's predicted trajectory. The leader and followers do not fail, and the followers follow the leader by communicating. There is no dynamic obstacle to the leader and followers. Two types of supervision are required here. One maintains the specified distance between the leader and the follower, and the other keeps the relative angle between them. A PID controller was used as the control method. PID coefficients were obtained via the trial-and-error method as follows: Kp = 1; Ki = 0.5; Kd = 0.5. These coefficients were used for both leaders and followers.  
The leader-follower approach was used for formation control, and the platoon approach was used as the formation type. In our study, a platoon formation was adopted as the formation type that expresses the positioning of the robots. In the platoon driving approach, each robot receives information only from the previous one, and all mobile robots move in a line as if they were a single object. According to the decision-making approach, a distributed system is preferred.  
The leader follows a set trajectory. The followers have to maintain a desired relative distance and orientation between them. In the environment used, the positions of the obstacles are fixed. The radius of the obstacle is taken as \(r\) = 1 m, and the distance to approach the obstacle is taken as \(\Delta g\) = 1 m at target positions, such as in front of and behind the obstacle. In this case, the robot can approach the center of the target up to 2 m. This is  
Figure 11: Leader–follower formation.  
valid for the target location. The robot can be closer to other obstacles as it moves forward. The distance between the leader robot and the follower is variable. The robot's maximum speed was set to 0.22 m/s, and its maximum rotation speed was 2.8 rad/s. Due to page limitations, only two test results are presented. These are in the form of a Turkish sentence containing one direct command and two interlinked statements in a sentence.