# BDS/IMU Integrated Auto-Navigation System of Orchard Spraying Robot
## 4 Discussion and Conclusions  
To address the unstableness of the satellite navigation system, which is caused by blocking, signal loss, and random error, an integrated navigation algorithm was built using the error Kalman filter that is based on measurements of position and heading angle to enhance the performance of the navigation system for long-term operation. The BDS and BDS/IMU integrated navigation system positioning tests were carried out in the closed orchard. The static experiments showed that the positioning error of the BDS was within 1.5 cm, the heading angle error was within 0.3\({}^{\circ}\), and the variance was 0.003223. The positioning error of BDS/IMU integrated navigation system was within 1.5 cm, the heading angle error was within 0.25\({}^{\circ}\), and the variance was 0.002052. The results indicated that the positioning and heading angle measurement performance of the BDS/IMU integrated navigation system was slightly better than that of BDS, which had more centralized data and better stability. The dynamic straight-line driving positioning experiments showed that the positioning error of BDS was within 5.29 cm, the heading angle error was within 3\({}^{\circ}\), and the variance was 0.5543. The positioning error of BDS/IMU integrated navigation system was within 2.49 cm, the heading angle error was within 2\({}^{\circ}\), and the variance was 0.237. These results implied that the performance of positioning and heading angle measurements of BDS/IMU integrated navigation system was significantly higher than that of BDS, and better than the integrated navigation system using Kalman filter with non-error observation. The kinematic model and pure tracking model of the pesticide robot were established, and the path tracking control algorithm of the sprayer robot was designed. The path planning was carried out in combination with the orchard terrain, and the navigation test was conducted in the closed orchard. The test results showed that when the operating speed of the sprayer robot was 0.4 m/s, the maximum error of linear tracking was less than 10.77 cm, and the average absolute error was 3.55 cm, which was superior to the tractor automatic navigation system based on DGPS (the maximum error of straight-line tracking is less than 15 cm) and the orchard sprayer automatic navigation system based on BDS (the maximum error of straight-line tracking is less than 13 cm). The field tests indicated that the auto-navigation system was appropriated to orchard spraying robots. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Line Number** & **Time/s** & **Maximum Error/cm** & **Minimum Error/cm** & **Average** & **Root Mean** \\  & & & & **Absolute Error/cm** & **Square Error/cm** \\ \hline
1 & 109.00 & 8.58 & 0.01 & 3.23 & 1.21 \\
2 & 108.01 & 9.36 & 0.06 & 2.96 & 0.35 \\
3 & 108.01 & 10.77 & 0.06 & 3.93 & 1.73 \\
4 & 108.01 & 9.98 & 0.11 & 4.16 & 2.37 \\
5 & 110.00 & 9.32 & 0.01 & 3.48 & 0.29 \\ Overall & / & / & / & 3.55 & 1.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The results of the navigation experiments in the citrus orchard. Figure 14: The navigation trajectory of the spraying robot. In the future, the BDS/IMU integrated navigation systems should be enhanced by integrating lidar and image sensors, which not only provide higher precision position and attitude data but also ensure the navigation functionalities, such as automatic obstacle avoidance and automatic in and out of warehouses, in orchards and agricultural machinery warehouses, when the tree crown or roof completely blocks the satellite signal. In addition, although the integrated navigation method based on Kalman filter can fuse the sensor information at different rates through the data synchronization processing method and calculate the navigation solution in real time, in order to maintain the data synchronization, it is often necessary to discard some measured values, resulting in a waste of information.