Path Planning of UAV in Oil and Gas Pipeline Based on Improved Genetic Algorithm
Aiming at the trajectory planning problem that occurs when oil and gas pipeline UAVs inspect the oil and gas pipeline network,an improved genetic algorithm based on adaptive population grouping was proposed.Firstly,the shortest flight path to com-plete all pipeline inspections was taken as the optimization objective,and the continuity of UAV inspections and avoidance of no-fly zones over oil and gas pipeline networks were taken as the constraints to construct a trajectory planning model for UAV inspections of oil and gas pipeline networks.Secondly,an adaptive population grouping strategy and an adaptive cross-variance operator were introduced,and the corresponding cross-variance methods were adopted for different populations.Lastly,the two types of oil and gas pipeline net-works were taken as inspection.Finally,two types of oil and gas pipeline networks were used as inspection objects,and comparative experiments were carried out based on the improved genetic algorithm,traditional genetic algorithm and genetic simulated annealing al-gorithm,respectively.The simulation results show that the improved genetic algorithm is better in the solution process and the solution results,and the average path lengths of the improved genetic algorithm have been reduced by 7.08％and 2.63％compared with those of the other two algorithms in the environment of higher complexity,which verifies the validity and universality of the proposed algo-rithms.
pipeline dronesoil and gas pipeline networktrajectory planninggenetic algorithm
万方数据
维普
