Near-Optimal 3-D Visual Coverage for Quadrotor Unmanned Aerial Vehicles Under Photogrammetric Constraints
Hongpeng Wang, Shiyong Zhang, Xiaoyang Zhang, Xuebo Zhang, Jingtai Liu
Abstract
In this article, we propose a complete visual coverage trajectory planning framework for quadrotor unmanned aerial vehicles (UAVs) in three-dimensional (3-D) terrain environment under photogrammetric constraints. To ensure the accuracy of the 3-D reconstruction, the air-to-ground projective geometric constraints are established. To optimize exploration efficiency, a novel two-step hierarchical coverage planning algorithm is implemented. The algorithm is verified in both simulation and practical experiments. The coverage trajectory that satisfies the constraints is generated, and the 3-D reconstruction from the images collected along the way is obtained. The results show that the proposed method can improve the performance of quadrotor UAV-based 3-D visual coverage in terms of trajectory length and traversal time, as well as the quality of 3-D reconstruction.