# SambotII: A New Self-Assembly Modular Robot Platform Based on Sambot
## 1 Introduction
### Related Works  
For SMRs that utilize the vision-based methods in autonomous docking, it is important to set proper target features, such as LEDs, special shapes, etc. Not only should the target features make the target robot module easily recognizable, but also it should provide enough information for distance/orientation measurement. Additionally, each docking module should have target features that can provide unique identification.  
As showed in Table 1 and Figure 1a, M-TRAN have five LEDs (two on its front face and three on its side face) as its target features. Depending on those LEDs, M-TRAN can determine the distance and orientation of the target-robot group, which consists of three M-TRAN modules and a camera module. However, this method cannot be used to simultaneously identify different robot groups, which means only one docking robot group can be recognized during the docking process. In each M-TRAN system, the captured images are processed by a host PC (personal computer). Because of the limitation in accuracy, the robot group has to form a special configuration to tolerate the docking error (see Figure 1b).  
The CKBot can achieve an autonomous docking process after the robot system exploded into three parts, each of which consists of four CKBot modules and one camera module. Some specific LED blink sequences are used as target features for the distance and orientation measurements. In this way, different disassembled parts of the robot system can be identified (see Figure 1c). However, this  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Name**} & \multirow{2}{*}{**Target Features**} & \multicolumn{2}{c}{**Capable of**} & **Image Processor** & **Location of the** \\  & & **Identifying** & **(Type)** & **Image Processor** \\ \hline \multirow{2}{*}{M-TRAN} & 5 white-colored & \multirow{2}{*}{No} & \multirow{2}{*}{X86 CPU (PC)} & \multirow{2}{*}{Outside robot} \\  & LEDs & & & \\ \hline \multirow{2}{*}{CKBot} & LED blink sequences & \multirow{2}{*}{Yes} & \multirow{2}{*}{PIC18F2680 (MCU)} & Camera module \\  & & & & of robot \\ \hline \multirow{2}{*}{UBot} & Cross label & \multirow{2}{*}{No} & \multirow{2}{*}{X86 CPU (PC)} & \multirow{2}{*}{Outside robot} \\  & on robot & & & \\ \hline \multirow{2}{*}{SambottII} & Combination of & \multirow{2}{*}{Yes} & \multirow{2}{*}{X86 CPU (Edison} \\  & color-changeable & & & module) \\ \cline{1-1} \cline{5-5}  & LEDs & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Existing self-assembly modular robot (SMR) systems that utilize the vision-based method.  
method costs too much time, because of the large number of images to be processed and the limited computing power of its PIC18F2680 MCU.  
For UBot, a yellow cross label is chosen as the target feature (see Figure 1d), by which the distance and orientation between the active and passive docking robot can be determined. Nevertheless, when the distance between the two docking surface is small enough, the UBot will use Hall sensors instead to guide the final docking process. In addition, the UBots are similar to the M-TRANs in two aspects: The images are processed by a host PC; and, different modules cannot be simultaneously distinguished.