Hybrid Strategy Selection and Polygon Decomposition for Energy-Aware 2D UAV Coverage Path Planning

Energy is the binding constraint on unmanned aerial vehicle survey missions, yet most coverage path planners commit to a single sweep pattern regardless of region shape. Our central contribution is to select decomposition granularity and the per-cell coverage pattern by a single physics-based energy criterion. A boustrophedon cellular decomposition with a controlled-concavity merge sets granularity; for each sub-polygon, the planner evaluates a minimum-width lawnmower and a shape-mimicking spiral and keeps the cheaper, with the undecomposed single-sweep solution always in the search space. On 50 benchmark polygons, at a 90% coverage floor, the hybrid reduces energy over a spiral baseline by a median 4.8% (ratio of means 11%) and is never dearer than either fixed pattern at floors of 90–99%. Which pattern is cheaper depends on geometry—lawnmower and spiral are not separable in aggregate (Wilcoxon p=0.47). A boundary-reflective zigzag for double coverage achieves 46% fewer turns and 18% less energy than boustrophedon 2×. The hybrid keeps the lowest mean energy under ±20% parameter perturbation and on larger fields with wider row spacing.