Rotary-wing unmanned aerial vehicles (UAVs) have been widely used in various fields such as power inspection，agricultural and forestry protection，and counter-terrorism rescue operation due to their exceptional flexibility and multifunctionality.However，the two-dimensional coverage issue caused by irregular terrain in complex planar areas presents significant challenges for path planning.To address this issue，this paper proposes a coverage path planning technology for UAVs in complex planar regions.During the region decomposition phase，an improved boundary-cutting decomposition (BCD) method is utilized to incorporate a directional tolerance parameter Δ

φ

during the merging of sub-regions to eliminate the redundant elongated areas generated by decomposition，which significantly reduces the frequency of backtracking in subsequent path planni

ng.In the coverage path generation phase，four innovative coverage modes (FF/FR/RF/RR) are designed，and the endpoints are dynamically configured.A multi-mode traveling salesman problem (MM-TSP) is constructed between sub-regions.By combining a candidate arrangement set Π

ϵ

generated from a relaxed TSP with a dynamic programming strategy，the computational complexity is reduced from

O

(

n

！·4

n

)to

O

(|π

ϵ

|·

n

·4

2

)，enhancing both computational efficiency and task coverage efficiency.Experimental results demonstrate that this coverage path planning technology reduces the average number of waypoints by 27.24%，shortens task distance by 26.12%，and decreases estimated task time by 26.20% across five scenarios：urban，airport，mountainous area，city，and forest.These findings validate the significant advantages of this technology in reducing the path redundancy and improving the task efficiency in complex planar regions，providing an efficient solution for the coverage path planning of rotary-wing UAVs.