TPPPA: A Triangular Partition Path Planning Algorithm for UAV Coverage in Irregular Areas

AV coverage planning is important in agricultural spraying, infrastructure inspection, and environmental monitoring. The task becomes more difficult when the target region contains concave boundaries or acute corners, since the planner has to avoid missed boundary areas while keeping the path short and flyable. Many decomposition based methods simplify such regions by filling concave parts or extending the boundary. This treatment may change the original area and lead to redundant scanning. This paper presents a Triangular Partition Path Planning Algorithm, named TPPPA, for coverage planning in known and static polygonal regions. The target area is first divided into triangular sub regions. In each triangle, the longest edge is selected as the scanning base, which reduces the corresponding height and the number of required scan channels under a given sensing radius. Adjacent triangles are connected through a side empty channel rule to reduce unnecessary transition segments. The generated waypoints are then adjusted by channel width checking and B-spline smoothing, so that UAV motion constraints, including the minimum turning radius, can be considered. The proposed method is evaluated in ROS and Gazebo using three irregular polygonal environments with 12, 18, and 24 vertices. Compared with concave filling, A*, RRT, and RRT∗ baselines, TPPPA reduces the total path length by 17% to 23% in the tested cases. The coverage rate remains between 99.8% and 99.9%. These results show that triangular partitioning with longest edge based scanning can improve coverage efficiency in static irregular areas, especially when acute corners are present.