## 3 Results
### Analysis of Orthogonal Experiments  
To better optimize the parameters and elucidate the interactions among the experimental factors, the ranges of various factors such as flexible claw closing speed, A, electric cylinder extending speed, B, and robotic arm movement speed, C, were determined through meticulous calculations and analyses. Subsequently, a three-factor and three-level quadratic regression orthogonal experiment was conducted, utilizing the net picking rate, N, and damage rate, Z, as the response values. The corresponding code for each experimental factor is listed in Table 2.  
The data were analyzed and processed using Design Expert software (22 version); the three-factor and three-level experiments were designed in accordance with [PERSON]'s experimental principle, as shown in Table 2.  
Utilizing Design Expert software (22 version), multivariate linear regression and quadratic fitting were conducted to determine the net harvesting rate, \(N\), and damage rate, \(Z\). Based on the data presented in Table 3, quadratic regression equations for both \(N\) and \(Z\) were derived. \[N=93.39-43.2A+16.3B-23.41C+240 AB+312.5 AC-31.25 BC-64A^{2}-101B^{2}-5.875C^{2} \tag{18}\] \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Coded Value**} & \multicolumn{3}{c}{**Factor**} \\ \cline{2-4}  & **Flexible Claw** & **Electric Cylinder** & **Speed of Movement** \\  & **Closing Speed,** & **Extending Speed,** & **of the Robotic Arm,** \\  & **A/(m/s)** & **B/(m/s)** & **C/(m/s)** \\ \hline \(-1\) & 0.02 & 0.05 & 0.1 \\ \(0\) & 0.05 & 0.15 & 0.2 \\ \(1\) & 0.1 & 0.25 & 0.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Encoding of experimental factors. \[Z=3.02875-30.7A+1.425B-1.475C+15 AB+10 AC-6.25 BC+206A^{2}+14B^{2}+4.125C^{2} \tag{19}\]  
The variance analysis of the regression equation simulation was carried out using Design Expert software (22 version) to obtain Tables 4 and 5; from Table 4, it can be seen that the net picking rate of the picking device was \(p<0.05\), suggesting that the regression model is statistically significant. Variance analysis demonstrated that the speed of flexible claw closure (\(p<0.0001\)) had a statistically significant impact on the net picking rate, and that the speed of the electric cylinder extension (\(p<0.05\)) exerted a notable influence on the net picking rate. Variance analysis demonstrated that the influence of each factor on the net picking rate, ranked in descending order of significance, was as follows: the speed of flexible claw closure, and the speed of electric cylinder extension. There was no significant effect of the mechanical arm movement speed. As is evident from Table 5, the quadratic regression model of the damage rate of the dragon-fruit-picking device is \(p<0.05\), indicating that the regression model was significant. Variance analysis demonstrated that the flexible claw closing speed (\(p<0.0001\)) has a very significant effect on the damage rate of dragon fruit and that the electric cylinder extending speed and the mechanical arm movement speed (\(p<0.05\)) had a significant effect on the damage rate of dragon fruit. Analysis of variance showed that the effects of the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Source** & **Sum of Squares** & **df** & **Mean Square** & **F-Value** & \(p\)**-Value** \\ \hline Model & 160.11 & 9 & 17.79 & 12.82 & 0.0014 \\ A—Flexible claw Closing speed & 108.78 & 1 & 108.78 & 78.42 & \textless{}0.0001 \\ B—Electric cylinder pushing speed & 0.0313 & 1 & 0.0313 & 0.0225 & 0.0089 \\ C—Speed of movement of the robotic arm & 0.0450 & 1 & 0.0450 & 0.0324 & 0.8622 \\ AB & 5.76 & 1 & 5.76 & 4.15 & 0.0081 \\ AC & 39.06 & 1 & 39.06 & 28.16 & 0.0011 \\ BC & 1.56 & 1 & 1.56 & 1.13 & 0.3238 \\ A\({}^{2}\) & 0.1078 & 1 & 0.1078 & 0.0777 & 0.7885 \\ B\({}^{2}\) & 4.30 & 1 & 4.30 & 3.10 & 0.1219 \\ C\({}^{2}\) & 0.2325 & 1 & 0.2325 & 0.1676 & 0.6945 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Analysis of variance regression equation of the net picking rate of dragon fruit.