Multi-period Coverage Path Planning and Scheduling for Airborne Surveillance


Corporate Authors
Defence Research and Development Canada, Centre for Operational Research and Analysis, Ottawa ON (CAN);McMaster Univ, Hamilton ONT (CAN)
In this paper, optimal surviellance mission plans are developed to cover disjoint areas of interest (AOIs) over an extended time horizon using multiple aerial vehicles. AOIs to be covered are divided into a number of cells. To promptly update information collected from AOIs and to ensure persistent surveillance, each cell is to be revisisted within a time slot. Joint path planning and temporal scheduling is formulated as a combinatorial optimization with the proposal of novel objective functions: 1) maximizing the minimum number of non-repeatedly covered cells in a sliding-window fashion and 2) maximizing the total number of covered cells in the mission plan. A multi-objective evolutionary algorithm (MOEA) with a specific chromosome representation and custom genetic operators, in which the constraint that each cell be revisited within a time slot is transformed into the third objective to handle infeasibility, is developed. The initial single-period paths are generated by solving a series of orienteering problems. The initial population is obtained by connecting these single-period paths and selecting the take-off time for each flight. Three mutation moves are proposed to enable revisiting in a single-period path and rescheduling of take-off time. The solutions converge in the MOEA and are selected by a weighted-sum model according to user preferences in decision making. Simulation results on different mission scenarios and different criteria show the superiority of the propo
Path planning;sensor scheduling
Report Number
DRDC-RDDC-2018-P106 — External Literature (P)
Date of publication
01 Aug 2018
Number of Pages
Reprinted from
IEEE Transcations on Aerospace and Electronic Systems, March 2018
Electronic Document(PDF)

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