## 1 Introduction  
OPTL, as a key component of the state grid infrastructure, is a primary means for the long-distance transmission of electric power, contributing significantly to the economic development of a stable nation. Due to their passage through harsh environments (e.g., deserts, mountains, forests, and rivers), OPTLs are easily affected by material deterioration, electrical flashover, and constant mechanical tension [1; 2; 3]. To efficiently and reliably transmit high-voltage electric power, OPTLs need to be routinely inspected for early fault detection [4]. In the US, the average cost of a half-hour blackout for medium and large industrial customers is USD 15,707, while it is nearly USD 94,000 for an 8 h interruption. Additionally, the growing global population and the over-reliance on electricity supply have created great demand for more efficient transmission line inspection strategies [5; 6]. The original inspection method for OPTLs was human inspection, which requires inspectors to climb along the power line to detect faults. This is laborious, inefficient, and dangerous for inspectors [7]; therefore, robots have become important tools for OPTLinspection over the past three decades [8]. Currently, many studies focus mainly on climbing robots (e.g., multi-arm robots) and flying robots (e.g., UAVs). Climbing robots are suitable for short-distance inspections with heavier payloads, providing detailed and reliable inspection data due to being closer to the power lines. Nevertheless, bypassing large obstacles and landing on overhead power lines present great difficulties. Flying robots are flexible, low cost, and capable of collecting high-quality images. However, they are limited in terms of flight endurance and cannot accurately inspect OPTLs from close distances [9; 10; 11]. Hybrid robots have been a focus of attention in recent decades, combining the advantages of climbing robots with those of flying robots. They are suitable for long-distance inspections with more flexibility. The flight mechanism can land on power lines and fly over obstacles, while the walking mechanism can walk along the OPTLs [12; 13]. The existing landing methods of hybrid robots only allow the robots to approach power lines from the top [12; 14; 15; 16] or the bottom [17; 18; 19]. However, these hybrid robots are unstable when walking on power lines due to their mechanical structure. In addition, power lines are flexible cable structures with slopes; when hybrid robots land on power lines, they may slip or lose control. As a result, autonomous landing methods for the developed FPLIR should be investigated to ensure safe landing on power lines. This challenge can be broken down into four main issues: (1) identify power lines in the observable space; (2) estimate the status of the robot using the onboard sensors; (3) plan a trajectory that satisfies the dynamic constraints of the robot; (4) track the trajectory under the work conditions [14]. To address these problems, this study proposes a novel landing method for the developed FPLIR based on prior structure data. The main contributions can be outlined as follows:  
Firstly, a novel approach is proposed for determining an SLA before landing on the line. The SLA is calculated based on prior structure data derived from the complex working conditions of the OPTLs. In addition, the SLA is considered to be the basis for a safe landing. Then, a trajectory planning method based on geometric constraints is applied. These constraints are defined by the landing characteristics, the structural features of the FPLIR, and prior structural data. By determining the desired position, the method generates a collision-free and dynamically feasible trajectory to guide the FPLIR to a zero-speed landing on the power line. Finally, an MPC controller is designed considering the characteristics of the FPLIR. The MPC controller applies a feedback control strategy to the generated landing trajectory and optimizes the trajectory in real time.