PL-RiskPlanner: Safety-Constrained Risk-Aware Path Planning for UAV Inspection in Simulated Power-Line Corridors
TL;DR
PL-RiskPlanner is proposed, a constraint-consistent framework that applies asset- and obstacle-specific checks before admitting grid edges, ranks the admitted edges using a power-line risk field, predicts moving-object positions at estimated UAV arrival times, and applies the same sampled verifier during smoothing.
Abstract
Path planning for power-line inspection requires asset-specific clearance from conductors, towers, and insulators, together with temporal separation from moving obstacles. Existing methods often optimize path length or a soft risk objective without showing that a single, explicit feasibility predicate is enforced during both search and postprocessing. We propose PL-RiskPlanner, a constraint-consistent framework that applies asset- and obstacle-specific checks before admitting grid edges, ranks the admitted edges using a power-line risk field, predicts moving-object positions at estimated UAV arrival times, and applies the same sampled verifier during smoothing. The contribution lies not in a new or faster A* search rule but in a power-line-specific feasible-set formulation that remains consistent across search, shortcutting, and final evaluation. A bounded margin accounts for uncertainty in velocity estimates. We evaluate eight executable planners across six synthetic scenario families and conduct controlled experiments on obstacle density, component ablation, risk weights, route crossings, prediction noise, and equal verifier budgets. Across 1800 nominal PL-RiskPlanner trials, no safety flag was recorded by the independent evaluator (Wilson 95% upper bound, 0.21%), and the mean verified-path length was 110.64 m. In controlled route crossings, the no-prediction variant produced 222 flags in 300 trials, whereas no safety flag was recorded for the complete planner. At velocity-noise level 0.4, the uncertainty margin changed the flag count from 203 to 47 and increased the mean simulator-reference dynamic clearance from −0.27 to 2.23 m. A 3600-trial equal-verifier-budget audit quantifies the resulting completion–computation trade-off without equating algorithm-specific iteration counters. Although the 50,400 trial records are specific to the stated simulator, they provide a reproducible protocol for safety-constrained inspection-path planning.