## 3 Simulation Analysis of Path Planning Algorithm Based on Improved Genetic Algorithm
### Field Experiment  
In order to verify whether the MCGA proposed is suitable for agricultural robot path tracking and operation, it is next used to plan the path of an actual land parcel, and an automatic navigation robot is used to track the planned path, which can verify the performance of the proposed MCGA. A suitable agricultural robot experimental system is built for tracking the planned path. The agricultural robot experimental system adopts car-like robots. As shown in Figure 5a, the chassis of the robot (Agilent Robotics Company, HUNTER-SE, Santa Clara, CA, USA) is an electrically rear wheel drive with front \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Field Size**} & \multicolumn{2}{c}{**Pathlength (m)**} & \multicolumn{2}{c}{**Number of Turns**} & \multicolumn{2}{c}{**Repetition (\%)**} & \multicolumn{2}{c}{**Coverage Rate**} \\ \cline{2-9}  & **GA** & **MCGA** & **GA** & **MCGA** & **GA** & **MCGA** & **GA** & **MCGA** \\ \hline \(70\times 20\) m & 1689.3 & 1507.2 & 96 & 82 & 23.1 & 6.707 & 85.63\% & 96.42\% \\ \hline \(50\times 10\) m & 615.2 & 499.4 & 35 & 28 & 10.6 & 3.7 & 87.52\% & 98.35\% \\ \hline \(30\times 5\) m & 182.7 & 136.1 & 11 & 7 & 8.3 & 2.6 & 90.5\% & 99.13\% \\ \hline \(10\times 3\) m & 54.6 & 43.3 & 9 & 5 & 6.5 & 0.8 & 96.4\% & 99.6\% \\ \hline \(6\times 3\) m & 28.5 & 20.3 & 6 & 4 & 3.4 & 0 & 99.4\% & 100\% \\ \hline \(4\times 2\) m & 12.5 & 9.3 & 4 & 3 & 2.2 & 0 & 100\% & 100\% \\ \hline Improve & & 21.8\% & & 6 & & 83.8\% & & 7.76\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of algorithm effectiveness between MCGA and GA.  
Figure 4: Path planning results of MCGA: (**a**) Path planning results; (**b**) Fitness value iteration curve. wheel electrically steering. The wheelbase of HUNTER-SE is 550 mm, the track width is 520 mm, its length is 820 mm, the width is 640 mm and the work width is 1 m. The minimum turning radius is 1.9 mm. As shown in Figure 5b, a navigation system (Shanghai Lianshi, RTK-GPS, Shanghai, China, positioning accuracy: 2.5 cm), radar sensor (Shenzhen SLAMTEC company, RPLidaR-A1, Shanghai, China), and IMU inertial sensor (Shenzhen WIT, HWT10 ICT-232, Shenzhen, China) are installed on the HUNTER-SE. After the automatic navigation robot platform is built, the Jiangsu University playground is selected as the experiment site for path planning and path-tracking experiments. As shown in Figure 6, the blue box represents the experimental area, which is 68 m long and 17 m wide. The latitude and longitude coordinates of the four boundary points are A (32.202038,119.509920), B (32.202160,119.510625), C (32.202013,119.510659), and D (32.201895,119.509959), respectively. The Pentagram symbol is the starting point of agricultural robot operation and the black squares are the divided grids in the figure. Due to the farm tools on a robot, the robot's operating width is set to 1 m, which means the size of each grid is 1 m \(\times\) 1 m. The initial parameters of the robot are set as follows: the speed is 0.5 m/s, the heading angle is 0, and the coordinate of the start point is (32.202010, 119.510658). The proposed MCGA is used to plan the robot's path in the experimental area, and the path coordinate points are output in the form of latitude and longitude. Figure 5: Robot platform construction: (**a**) Robot chassis; (**b**) Robot with GPS navigation system. Figure 6: Test site map. The robot's state parameters need to be collected during the experiment. Considering that ROS (Robot Operating System) is an open-source operating system suitable for robot development, it provides a structured communication layer on top of the host operating system of heterogeneous computing clusters [22]. The Rosbag tool of the ROS framework can provide an effective method for recording, replaying, analyzing, and processing data. By capturing data streams, the Rosbag can help researchers and developers quickly reproduce experimental scenarios based on offline data in repeatable, low-cost analysis, and debugging.