# Automatic Extraction of High-Voltage Power Transmission Objects from UAV Lidar Point Clouds
## 1 Introduction  
Transmission line inspection and maintenance are crucial aspects of power resource management [1]. A power transmission corridor generally includes high-voltage (HV) towers, attachments (e.g., insulators), and transmission wire, as well as vegetation, buildings, and other environmental objects on the ground. As an important part of the transmission system, HV towers not only play a mechanical supporting role for the long-distance conductor, but also serve as the nodes of connections or turning points, realizing large-scale deployment of power resources over a long distance. Similarly, as the pipeline for electric power, transmission wires are important carriers of power resources. Key power transmission elements like HV power pylons and wires are joinedtogether and connected with isolators. They are mostly located in remote environments with harsh terrains, e.g., deep forests, which require great effort to maintain. To guarantee the safety and reliability of power transmission systems, power companies have to ensure that these components maintain sufficient safety margins from the surroundings. One routine risk-management job is power corridor inspection. Traditionally, inspections of the HV transmission corridors have mainly relied on laborious and dangerous human work using aerial- and ground-based devices (e.g., telescopes and video/infrared cameras) [2]. Corridor inspections by these traditional techniques are neither efficient nor effective, as the subjective judgements rely heavily on experience. As an important part of remote sensing, airborne remote sensing is an efficient and flexible technology to obtain large-coverage, high-precision measurements compared to ground-based techniques. The up-to-date airborne remote-sensing data mainly include synthetic aperture radar images, optical images, thermal images, and laser scanning point clouds [3]. Compared to aerial images, light detection and ranging (Lidar), or laser scanning data, in the form of point clouds, provide the spatial coordinates of objects in 3D with higher accuracy [4; 5]. Information on intensity and multi-return echoes is often available. By using Lidar, the 3D surface information of observed objects, such as their geometric structure and semantic information, can be effectively derived [6; 7]. Airborne Lidar inspection of the transmission corridor at close range enables the detection of detailed condition information of the power corridor in 3D, such as the accurate geometry of power lines and spatial distribution of pylons [8]. Their risk states can then be analyzed by a series of construction, modeling, and assessment, which contributes to the corridor's safety maintenance [9]. The use of unmanned aerial vehicles (UAVs) carrying new sensors for electric power inspection has been developed largely since the end of the 20 th century [10]. Given that the HV power line (PL) facilities in remote or harsh environments are generally difficult to reach, UAV mapping presents huge advantages by saving manpower and producing more reliable results. UAV systems have been increasingly used by communities due to their low cost, less strict requirements for take-off and landing, and their ability to load different types of sensors (e.g., camera and Lidar) [11]. As a light-weight and close-range airborne laser scanning (ALS) technology, UAV Lidar, usually equipped with middle-sized or small laser sensors, has been rapidly developed for transmission line inspection as a time-saving and cost-friendly solution. It can directly generate dense point clouds in 3D with a higher level of precision compared to aerial optical imagery and video [5; 12; 13], because image-based techniques can produce noisy results from the stereo-matching stage [14]. According to comparative studies of power line monitoring, the accuracy of height estimation for poles and trees is clearly better when using UAV Lidar data than aerial images [4; 15]. Compared to robotic inspection [16], UAVs have higher flexibility and larger coverage.