# Development of a Capsule-Type Inspection Robot Customized for Ondol Pipelines
## 2 Literature Review  
Pipelines are the safest, most economical, and most widely used methods for transporting fluids in industrial and residential settings [3]. Internal and external aging and contamination can cause performance degradation and increase operational costs, underscoring the critical importance of regular inspections [9]. Therefore, regular inspections are necessary to maintain the proper functionality and cost efficiency of pipelines [10; 11]. Consequently, research on robots for inspecting pipeline interiors has garnered increasing interest [12; 13]. The use of pipeline inspection robots can improve efficiency compared to traditional manual methods, including visual inspections. Such robots can replace labor-intensive and hazardous tasks while enhancing productivity in maintenance operations through capabilities such as data collection and cleaning [14; 15]. Research on internal inspection robots for pipelines can be categorized into two main areas: review studies identifying technological trends in pipeline robots and studies proposing driving mechanisms and developing robots according to the purpose, diameter, and shape of pipelines. First, review studies have continually examined various types of pipeline robots based on diverse characteristics, including inspection accuracy, adaptability to size and shape, flexibility, vertical mobility, scalability, cost, speed, design complexity, impact on pipelines, and movement efficiency [1; 2; 3; 9; 10; 11; 14; 15; 16; 17; 18]. Additionally, studies focusing on specific driving mechanisms, such as wheel-based [12], wall-pressing [13; 19], hybrid [20], and worm-like [21] methods, have analyzed technological trends. Research on the direct development of robots is ongoing. Table 1 summarizes the studies that have designed and developed driving mechanisms suitable for specific pipeline purposes and sizes. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Authors** & **Power Supply** &
\begin{tabular}{c} **Driving** \\ **Mechanism** \\ \end{tabular} & **Use** & **Pipe Size (mm)** \\ \hline [PERSON] and [PERSON] (2007) [22] & Cable & Diameter-adaptive & Gas pipelines & \(\sim\)400–600 \\ \hline [PERSON] et al. (2020) [23] & Cable & Diameter-adaptive & Pipelines and duct & \(\sim\)60–90 \\ \hline [PERSON] and [PERSON] (2018) [24] & Battery & Diameter-adaptive & Gas pipelines & \(\sim\)63–125 \\ \hline [PERSON] et al. (2011) [25] & Cable & Wheel-type & Not specified & 80–100 \\ \hline [PERSON] et al. (2015) [26] & Cable & Wheel-type & Boiler pipelines & 45 \\ \hline [PERSON] et al. (2014) [27] & Battery & Wheel-type & Not specified & 100 \\ \hline [PERSON] et al. (1999) [28] & Cable & Wheel-type & Gas pipelines & \(25,50,150\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Existing studies proposing and developing pipeline inspection robots. Previous studies have targeted pipelines with diameters ranging from 25 to 1440 mm, proposing various driving mechanisms to navigate different pipeline configurations, including horizontal, vertical, inclined, and curved pipes. Representative driving mechanisms include diameter-adaptive [22; 23; 24], wheel-type [25; 26; 27; 28; 29; 30], ball-type [31; 32; 33], bug-type [34], and crawler-type [35] robots. The performance of these robots has been validated through field applications and laboratory tests. Each type of robot offers specific advantages, such as fast horizontal mobility, but also presents certain drawbacks, such as unsuitability for inclined and curved pipes, slower speeds, or the need for cable connections for power supply [35]. A study by [PERSON] and [PERSON] [32] and a study by [PERSON] [33] proposed an autonomous, free-swimming spherical device called SmartBall(r) (Pure Technologies, Calgary, AB, Canada). This device is designed to detect leaks and assess conditions in large-diameter pipes. It travels through the pipeline, collecting acoustic data to identify leak locations and pipe wall conditions with high precision.