Lo, Kin MingKin MingLoLo, Leung YauLeung YauLoWong, Pak-KanPak-KanWongProf. LEUNG Kwong Sak2023-02-222023-02-2220182018 3rd International Conference on Control, Robotics and Cybernetics, CRC 2018 8780047, pp. 67-72http://hdl.handle.net/20.500.11861/7421Applications using multiple quadcopters such as environment detection or packet delivery have drawn lots of interest from commercial companies. As the battery life of a quadcopter is very limited, a path planning algorithm can help to improve the efficiency of each flight. To avoid overloading some quadcopters while under-utilizing the others, the algorithm will minimize the total path lengths and balance individual path length. This problem is formulated as multi-objective multiple traveling salesman problem (MOMTSP). To generate flight paths quickly for commercial application, City Quadcopter Path Planner (CQPP) which is based on Non Sorting Genetic Algorithm II (NSGA-II) is proposed and applied to search for the solutions. Positive results are obtained from three benchmark scenarios, which are designed for testing the performance of the algorithm in solving this path planning problem.enPath PlanningUrban CitiesPath LengthFlight PathTraveling Salesman ProblemBenchmark ScenarioComputation TimeTarget LocationRandom LocationsAerial VehiclesUnmanned Aerial VehiclesMulti-Objective OptimizationEdge WeightsSingle ObjectTravel CostsPathfindingPart Of ChromosomeGenetic OperatorsPopulation Of SolutionsEfficient PathNo-Fly ZoneSwap OperationCost PathConference Paper10.1109/CRC.2018.00022