# Research on Path Planning Multiple Mobile Robots Based on the LAPGWO Algorithm
## 4 Results
### Physical Experiment Platform  
To verify the practical applicability of the method proposed in this paper, a small mobile robot independently built by the research group is used for a physical experiment. The experiment adopts a distributed structure. The main control center calls the global camera to identify the ArUco tags on the top of the mobile robots to obtain their positions, and the position information is fed back to the controllers of each mobile robot in real time. The robots will receive the transmitted position and global map information in real time. The robots share their pose information, autonomously calculate the generated trajectory, and perform obstacle avoidance according to the information. Considering the computing power of the small mobile robots, all data are calculated on the central controller, and the calculation results are transmitted to each small robot to achieve the effect of distributed control. The physical experiment platform mainly includes a central controller, a visual recognition part, and mobile robots. The visual recognition uses the ArUco (augmented reality University of Cordoba) tag technology. The ArUco tag is square, with a black background, and the white rectangle inside stores numerical numbers and other information in a specific encoding. Each robot is pasted with a given ArUco tag in this section's physical experiment. The camera identifies the ArUco tag on the robot and transmits the information to the control platform. After receiving the information, the control platform processes the information to determine the position information and number information of each robot. The information is displayed visually on the upper computer interface, which is convenient for debugging and data analysis. The structural composition diagram of the experimental robot is shown in Figures 17 and 18. Figure 9 shows the pose recognition effect of the experimental robot. The experimental platform is composed of miniCup robots and a central controller, which can effectively identify the pose information of the robots. The upper computer identifies the ArUco tags through the camera to obtain the two-dimensional pose information of each robot. It transmits the real-time pose information of each robot to each robot through the local area network. Due to the computing power problem of the robots, in this section, the  
Figure 16: Results of significance test. central controller will carry out unified processing, plan the path, and output the results to each robot to achieve the effect of distributed control. Due to the limited experimental conditions, the physical experiment environment in this section is verified based on the above simulation experiment. The verification map is shown in Figure 19, which is a physical warehouse environment. The size of the experimental map is simulated and built as \(1/100\) of the actual simulation environment. Figure 19: Physical warehouse testing environment. Figure 17: Structural composition diagram of the experimental robot. Parchment paper is used as the driving road surface to eliminate the interference of other factors. The road surface is a rectangle with a length of 1.8 m and a width of 0.9 m, and cartons replace the warehouse shelves. The robots are randomly distributed on the map and move autonomously from the starting point to the target point. The robot numbers range from 0 to 7, corresponding to numbers 1 to 8 in the simulation. The respective initial position coordinates are (0.042 m, 0.049 m), (0.418 m, 0.042 m), (0.046 m, 0.591 m), (1.104 m, 0.061 m), (1.197 m, 0.849 m), (1.687 m, 0.218 m), (0.152 m, 0.851 m), and (0.799 m, 0.861 m). The target point coordinates are (1.409 m, 0.848 m), (1.481 m, 0.620 m), (1.178 m, 0.333 m), (0.404 m, 0.861 m), (1.511 m, 0.044 m), (0.418 m, 0.855 m), (1.311 m, 0.052 m), and (0.316 m, 0.040 m) in turn.