# Robot Delay-Tolerant Sensor Network for Overhead Transmission Line Monitoring
## 1 Introduction  
The smart grid is a move to upgrade traditional power systems to modern power grids with a high level of automation [1]. An electric power system consists of numerous elements. If the power elements fail, it will cause huge economic losses. With economic development, the power grid is expanding rapidly. Firstly, power lines have been expanded into harsh environments, increasing the difficulty of communication and monitoring [2]. Secondly, due to the increase of electricity demand, complex towers with multi loops are used more frequently, increasing the difficulty of fault detection and making inspection more dynamic and specific [3]. It is urgently necessary to adopt advanced equipment and methods to monitor the power grid effectively. Therefore, it is of great practical significance to research intelligent monitoring and communication systems for transmission lines [1, 4]. At present, power grid inspection is mainly conducted by human inspection, robot inspection and remote monitoring network based on Wireless Sensor Network (WSN), etc. [5, 6]. With large-scale construction of grids in remote areas, efficiency of human inspection is too low to meet requirements. In recent years, the rapid development of robot technology and WSN technology has stimulated the application of robot inspection and large-scale sensor monitoring system in smart grids. The inspection of power lines by robots will reduce the manpower and check errors, and improve the efficiency of inspection. Usually, a robot can only communicate with a control device over a shortdistance, which greatly restricts the large-scale application of robot inspection. WSN, as a practical remote monitoring technique, has received extensive attention. The existing remote monitoring system for power grids relies on the large-scale deployment of fixed sensors and communication nodes, with high maintenance cost, low fault tolerance and less scalability. Furthermore, there is no flexibility in the grid fault detection. To sum up, there are still many problems that restrict the development of intelligent monitoring for a power grid. In an early piece of research, a robot inspection system was developed to realize the automatic inspection of power lines [6; 7]. The inspection robot walks on the high-voltage transmission line to sense and locate faults, sending the acquired data to a mobile monitoring station (MMS) on the ground. The communication between the robot and MMS is achieved via Wi-Fi (IEEE 802. 11 n) with a moving antenna incorporated in the robot. The MMS has 3G/4G communication capabilities and it sends the data to the CMP (control and monitoring platform) through this channel. Once the CMP receives the data, it will analyze the anomalies or potential faults. The system was tested in Guangdong and Jilin provinces of China, and the project running is presented in Figure 1. However, there were some communication failures of the system in the tests conducted in the primordial forests of Jilin. Communication capabilities between the robot and the MMS were down and communication from the MMS to the CMP did not work, because of disturbance of the trees. Real-time performance and reliability are two important indices in the monitoring systems of power grids and other scenes [8]. However, the endlessness of transmission lines makes it difficult to monitor the whole grid in real time. The real-time-based monitoring of transmission lines requires large-scale deployment of nodes to form complex Wireless Sensor Network (WSN) systems [9], which may lead to financial burden or uncontrollable risks. Nowadays the monitoring of transmission lines is mainly based on two methods, i.e., real-time monitoring for the important components or inspection for the whole line. The inspection of transmission lines is mainly conducted by humans, unmanned aerial vehicles (UAVs) and robots [10; 11]. The main contents of inspection data are images and videos of transmission lines and surrounding environment.