A challenge for inspecting transmission power lines with Unmanned Aerial Vehicles (UAVs) is to precisely determine their position and orientation, considering that the geo-location of these elements via GPS often needs to be more consistent. Therefore, a viable alternative is to use visual information from cameras attached to the central part of the UAV, enabling a control technique that allows the lines to be positioned at the center of the image. Therefore, this work proposes a PID (proportional–integral–derivative) controller tuned through interval type-2 fuzzy logic (IT2_PID) for the transmission line follower problem. The PID gains are selected online as the position and orientation errors and their respective derivatives change. The methodology was built in Python with the Robot Operating System (ROS) interface. The key point of the proposed methodology is its easy reproducibility, since the designed control loop does not require the mathematical model of the UAV. The tests were performed using the Gazebo simulator. The outcomes demonstrated that the proposed type-2 fuzzy variant displayed lower error values for both stabilization tests (keeping the UAV centered and oriented with the lines) and the following step in which the trajectory is time-variant, compared to the analogous T1_PID control and a classical PID controller tuned by the Zigler–Nichols method.

Nowadays, UAVs are used in several industrial applications so indoors and outdoors environments. The main objective of this paper is to propose a control strategy applied to UAVs using line-following and computer vision. In this way, this paper presents a Non-linear Model Predictive Control (NMPC) combined with a PID controller aiming to provide smooth control actions. To evaluate the model robustness, the authors perform simulations in environments containing flaws in the visual segments. The control scheme presented in this paper has a better performance when compared to the NMPC standalone or classic control strategies such as PID.

The use of robots for inspection of transmission lines has been the target of several studies nowadays, allowing the replacement of manual supervision. The goal of this paper is to present a strategy for the estimation of a trajectory for the tracking of UAVs on these power lines based on the Hough Transform with the iterative RANSAC method. The purpose of this calculation is to define the parameters that will be inserted into the NMPC Control that will determine the required control actions to solve the visual path tracking problem. Practical tests show that the proposed method was effective with the UAV maintaining the trajectory with low errors.