| CPC G08G 5/0017 (2013.01) [G08G 5/045 (2013.01)] | 15 Claims |
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1. A method of coordinating a number of unmanned aerial vehicles (UAVs) to be deployed in a region under a set of constraints, the method comprising:
obtaining constraint data that is indicative of the set of constraints under which the number of UAVs are configured to fly in the region, the constraint data indicating, when the number of UAVs fly in the region, requirements to be satisfied with respect to a safety distance between UAVs, a safety distance between an UAV and an obstacle, an UAV altitude limit, and an UAV speed limit;
defining a cost function having (1) an UAV energy consumption term that is indicative of an energy consumption of each UAV for flying from a source location to a destination location along a given flight path, and (2) a set of cost terms that correspond to the set of constraints;
executing an UAV-capacity maximization function to determine a maximum UAV number of a group of UAVs that is able to fly in the region without violating any constraint of the set of constraints by:
(1) setting an UAV number of the group of UAVs at an initial value,
(2) iteratively performing:
(i) based on the defined cost function, applying a modified Particle Swarm Optimization algorithm to determine flight paths for the group of UAVs, and
(ii) updating the UAV number by adding a predetermined incremental value to the UAV number of a previous iteration,
until the requirement with respect to the safety distance between UAVs or the requirement with respect to the safety distance between an UAV and an obstacle is violated, and
(3) determining the updated UAV number as the maximum UAV number;
transmitting the determined flight paths to a group of UAVs that has the determined maximum UAV number of UAVs; and
monitoring flight paths of the group of UAVs and adjusting the flight paths of the group of UAVs based on the transmitted flight paths, to ensure that all UAVs in the group operate in the region without violating any constraint of the set of constraints,
wherein:
by applying the modified Particle Swarm Optimization algorithm, the flight paths of the group of UAVs are determined to minimize the energy consumption,
an initial position and velocity of each particle of the modified Particle Swarm Optimization algorithm are determined using chaos-based initialization, and
for each iteration of the modified Particle Swarm Optimization algorithm, an inertia weight and an acceleration coefficient are adjusted based on a current iteration count and a predetermined maximum iteration number.
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