# Research Progress on Synergistic Technologies of Agricultural Multi-Robots
## 3 Research Progress on Synergistic Technologies of Agricultural Multi-Robots
### Communication  
Communication is the basis of information interaction and collaboration among multiple robots. In agricultural production, many factors affect the fine operation of agricultural robots, and to maintain coordination and cooperation among multiple robots and to gain a more comprehensive understanding of the environment in which multiple robots perform tasks, robots need to interact with each other through information to better perform a given task [29]. [PERSON] and [PERSON] concluded that even a small amount of communication can improve the performance of multi-robot systems tremendously through experiments [125]. At present, the communication technology of agricultural multi-robots mainly involves three parts: multi-robot communication mode, communication network, and communication protocol. * Communication mode  
The multi-robot communication mode is divided into three categories from a macro perspective: explicit communication, implicit communication, and explicit and implicit communication, as shown in Figure 17. Explicit communication is an interactive mode \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Formation Control Method** & **Advantages** & **Disadvantages** & **Steps** & **Application** \\ \hline Bidirectional Weighted & Simplified description and assignment of tasks; Weighted & Difficult to handle fault tolerance; Weighted & Defining the dynamic model of the virtual structure; Transforming the overall movement of the structure into the motion of the robot; & & \\ Constraints & accuracy; & Low mobility limits range of motion; & Obtain the tracking control law of each robot; & & \\ \hline Graph theory approach & & Suitable for large-scale robot formation; Easy addition and design to change between different formations; & The implementation is more complicated, mainly limited to simulation research; & Define the formation right map & \\ \hline \multirow{4}{*}{Artificial potential field} & Little calculation; robot formation; Easy to implement real-time control; Easy to handle collision avoidance problems in obstacle spaces; & The design of the potential field function is difficult; Problem with local extreme points; & Design artificial potential field (environment and constraints between robots in the formation); Precision irrigation in the vineyds [72] \\ \hline \multirow{4}{*}{Model predictive control (MPC)} & Has a strong theoretical foundation; Adds multiple constraints in the control process, and optimizes the control sequence by online scrolling optimization combined with feedback correction of real-time information; & Real-time planning formation retains the reference center and target control amount of each robot; & Tracked fish (simulation) control of each robot; & [117] \\ \hline \multirow{4}{*}{Leader-follower} & \multirow{4}{*}{Simplified system control;} & The ability to adapt to a dynamic environment is not strong. If the leader fails, the entire system crashes; & Identify leading robot and formations; A follower follows the leader Control the spacing between the leading robot and the following robot-angle (\(l-\varphi\)) or lateral spacing-longitudinal spacing (\(l-l\)); & Collaborative air-ground surveillance [122] \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of formation control methods [34; 41; 75; 86; 104; 106; 109; 111; 113; 114; 117; 123; 124]. through communication as a medium, requiring a clear communication protocol between interacting parties. This method is often used for concordant communication among robots, but it incurs fairly large costs. Implicit communication is the acquisition of the required information through the external environment and internal sensors without an explicit exchange of data, so some advanced coordination strategies cannot be used, which affects the capacity to perform certain complex tasks.