# The Development of Rubber Tapping Machines in Intelligent Agriculture: A Review
## 4 Rubber Tapping Technology
### Automatic Tapping with Self-Propelled Robot  
[PERSON] et al. [18] proposed a rubber tapping robot for natural rubber plantations and developed an integrated end-effector to further accurately perceive the tapping trajectory and tapping operations. The adaptability of the upgraded trajectory and the accuracy, as well as the efficiency of the starting point positioning algorithm, were verified by field experiments on a rubber plantation. Alignment error and execution time curves are shown in Figure 9. Overall, the alignment error was around 1.0 \(\pm\) 0.1 mm, and the execution time was 17.01 \(\pm\) 3.65 s. As shown in Figure 10, the accuracy of chip thickness and chip width was about 1.73 \(\pm\) 0.28 mm, and 5.07 \(\pm\) 0.13 mm, respectively. Furthermore, the accuracy \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Traditional Tapping Knife**} & \multicolumn{2}{c}{**Electrical Tapping Knife**} \\ \cline{2-5}
**Parameter Type** & **Push-Type** & **Pull-Type** & **4 GXJ-1** & **4 GXJ-2** \\ \hline Power & Manpower & Manpower & Brushless motor & Brushless motor \\ Cutting time per tree (s) & 12–18 & 12–18 & 10–16 & 5–10 \\ Bark consumption (mm/year) & 110–150 & 110–150 & 110–130 & 110–130 \\ Battery capacity (mAh)/Endurance (h) & - & - & 2000/1.5–2.0 & 4000/3.5–4.5 \\ Cost of training time for rubber tappers (d) & 25–30 & 25–30 & 3–5 & 3–5 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance comparison between the traditional tapping knife and the electrical tapping knife [67]. of the chip weight was 1.99 \(\pm\) 0.24 mm. The average operating time of the whole tapping operation was 80 \(\pm\) 5 s. That study demonstrated the potential of applying industrial robotics to the field of latex harvesting. Moreover, researchers have also presented a method of tapping with a guide-positioning-type screw track [62]. This model uses a spiral track to realize a spiral tapping track, which is advantageous to the flow of latex. This study demonstrates the potential of applying industrial robotics to the field of latex harvesting. At present, there is growing interest in research on the autonomous operation of self-propelled rubber tapping machines. Moreover, this kind of robot has a tremendously marketable value and potential [69; 70]. As shown in Figure 11, the development of a self-propelled rubber tapping machine usually requires the fusion and testing of various technologies, such as navigation, sensor perception, and automatic control. The development of an autonomous navigation technique is of great importance to the automatic movement of a self-propelled rubber tapping machine, especially in night-time operations [71]. Path planning through rubber forests is necessary in order to meet the requirements of agricultural norms and to look for reasonable walking tracks on the premise of nonredundant and non-leaking operations. Figure 8: Diagram of experiment results. The change in the color of the graph from blue to red indicates the change in the ordinate from less to more. (**a**) Interaction response surface [59]; (**b**) response surface diagram of cutting angle and cutting depth (left), and response surface diagram of cutting angle and bark consumption thickness (right) [58]. Figure 9: Curves of multiple threshold pair test results: (**a**) pixel deviation—alignment error results, (**b**) cutting feed—alignment error results, (**c**) pixel deviation—execution results, and (**d**) cutting feed—execution results [18]. Path planning for navigation in rubber orchards commonly involves global path planning and local path planning (Table 4). Local path planning requires real-time feedback. It is used for local obstacle avoidance in path planning [72] and local tracking path planning [62; 73; 74] is based on sensing the external environment through sensors and feeding information back to the controller for real-time path control decisions [75]. Global path planning is a planning method that requires the complete path information of a rubber forest as prior data [76; 77; 78].