Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7421
Title: Multi-objective Multiple Quadcopter Path Planning in Urban City
Authors: Lo, Kin Ming 
Lo, Leung Yau 
Wong, Pak-Kan 
Prof. LEUNG Kwong Sak 
Issue Date: 2018
Publisher: IEEE
Source: 2018 3rd International Conference on Control, Robotics and Cybernetics, CRC 2018 8780047, pp. 67-72
Conference: 2018 3rd International Conference on Control, Robotics and Cybernetics, CRC 2018 
Abstract: Applications 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.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/7421
DOI: 10.1109/CRC.2018.00022
Appears in Collections:Applied Data Science - Publication

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