Unmanned Aerial Vehicle Positioning Algorithm Based on the Secant Slope Characteristics of Transmission Lines

Abstract

Aiming at the problem of positioning consistency and real-time performance during power inspection of unmanned aerial vehicles (UAV), this paper proposes an UAV positioning algorithm based on the secant slope characteristics of transmission lines. The traditional correlation scan matching (CSM) positioning method is prone to mismatch under the condition of a single geometric feature. Although the inertial measurement unit (IMU) -aided CSM method improves the positioning accuracy, using the IMU for a long time to estimate the position is prone to cumulative errors and increases the computational cost to a certain extent. Our proposed method uses the least square polynomial curve fitting method to parametric reconstruction of the transmission line, which enhances the geometric characteristics of the transmission line and made up the missing part. The secant line of transmission line is extracted and its feature is parameterized to match with the reconstructed transmission line map, and the translation vector and rotation vector of UAV are estimated. Through multiple sets of experiments, it is proved that our algorithm is less than the CSM method and the IMU-aided CSM method in terms of average translation error, average rotation error, and positioning time. Our algorithm not only improves the positioning accuracy but also guarantees the real-time positioning requirements.

Keywords

• Cumulative error
• point cloud matching
• secant slope
• transmission line