Abstract
This paper considers a reconnaissance task assignment problem for multiple unmanned aerial vehicles (UAVs) with different sensor capacities. A modified Multi-Objective Symbiotic Organisms Search algorithm (MOSOS) is adopted to optimize UAVs’ task sequence. A time-window based task model is built for heterogeneous targets. Then, the basic task assignment problem is formulated as a Multiple Time-Window based Dubins Travelling Salesmen Problem (MTWDTSP). Double-chain encoding rules and several criteria are established for the task assignment problem under logical and physical constraints. Pareto dominance determination and global adaptive scaling factors is introduced to improve the performance of original MOSOS. Numerical simulation and Monte-Carlo simulation results for the task assignment problem are also presented in this paper, whereas comparisons with non-dominated sorting genetic algorithm (NSGA-II) and original MOSOS are made to verify the superiority of the proposed method. The simulation results demonstrate that modified SOS outperforms the original MOSOS and NSGA-II in terms of optimality and efficiency of the assignment results in MTWDTSP.
Highlights
Unmanned aerial vehicles (UAVs) have played increasingly important roles in military reconnaissance during the last decade
Compared with the mixed-integrated linear programming (MILP) form, Multiple Time-Window based Dubins Travelling Salesmen Problem (MTWDTSP) takes into account the influence the influence of various flight paths on the assignment results; as for compared with common travelling salesman problem (TSP) form, MTWDTSP could deal with the effect of different time windows on task sequence
We introduce a modified multi-objective symbiotic organisms search (MOSOS) [27] to solve the MTWDTSP with dynamic time window constraints, task type constraints, and UAV sensor constraints
Summary
Unmanned aerial vehicles (UAVs) have played increasingly important roles in military reconnaissance during the last decade. To describe the CTAP, a novel cooperative reconnaissance task assignment model for multi-UAV is formulated: multiple time window-based Dubins travelling salesmen problem (MTWDTSP). Compared with the MILP form, MTWDTSP takes into account the influence the influence of various flight paths on the assignment results; as for compared with common TSP form, MTWDTSP could deal with the effect of different time windows on task sequence. In this particular problem, heterogeneous reconnaissance targets are presented as point, strip, and surface targets, according to the features of targets and the performance of UAV sensor.
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