Multi-objective Multiple Quadcopter Path Planning in Urban City
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AbstractApplications 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.
All Author(s) ListKin-Ming Lo, Leung-Yau Lo, Pak-Kan Wong, Kwong-Sak Leung
Name of ConferenceThe 3rd International Conference on Control, Robotics and Cybernetics
Start Date of Conference18/12/2018
End Date of Conference20/12/2018
Place of ConferencePenang
Country/Region of ConferenceMalaysia
Year2018
LanguagesEnglish-United States
KeywordsPath planning, Quadcopter, Genetic Algorithm, Multi-objective multiple traveling salesman problem

Last updated on 2019-06-05 at 15:11