UAV DECISION AND CONTROL SYSTEM
First Claim
1. A hierarchical multiple UAV decision and control system comprising two or more armed UAV'"'"'s dispatched onto a theater environment in order to search, detect and attack time-critical attack targets, and at least two of the following means:
- (i) flocking means based on a behavioral heuristic algorithm wherein said algorithm controls the velocity and heading of the UAV'"'"'s and is configured so that each UAV communicates with its closest neighbors only, and control information comprising flocking data propagates from node to node using a tree management or hierarchical protocol;
(ii) wireless ad-hoc communications means between the UAV'"'"'s as follows;
for communicating attack target list and flocking information both from the root downstream towards other nodes in the sub-trees and from each node upstream towards the root;
the root node gathers task assignment and flocking data calculated by its sub-trees, calculates global functions, task assignment and flocking data for the tree;
the root node distributes said global functions, task assignment and flocking data back to its sub-trees;
in conditions where communication between the UAV'"'"'s is constantly disrupted due to dynamic changes in the field, the constant flow of upstream and downstream data improves the overall efficiency of the UAV'"'"'s in the tree; and
(iii) task assignment means configured so that each UAV, using a graph-theoretic approach, locates all detectable attack targets;
identifies said attack targets;
computes the distance to each of said attack targets; and
produces an attack plan based on system parameters, such that said attack plan optimizes the distances between said UAV'"'"'s to said attack targets.
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Accused Products
Abstract
The present invention relates to a hierarchical system and method for task assignment (TA), coordination and communication of multiple Unmanned Aerial Vehicles (UAV'"'"'s) engaging multiple attack targets and conceives an ad-hoc routing algorithm for synchronization of target lists utilizing a distributed computing topology. Assuming limited communication bandwidth and range, coordination of UAV motion is achieved by implementing a simple behavioral flocking algorithm utilizing a tree topology for target list routing. The TA algorithm is based on a graph-theoretic approach, in which a node locates all the detectable targets, identifies them and computes its distance to each target. The node then produces an attack plan that minimizes the sum of distances of the UAV'"'"'s in the subtree of a given node to the targets.
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Citations
22 Claims
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1. A hierarchical multiple UAV decision and control system comprising two or more armed UAV'"'"'s dispatched onto a theater environment in order to search, detect and attack time-critical attack targets, and at least two of the following means:
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(i) flocking means based on a behavioral heuristic algorithm wherein said algorithm controls the velocity and heading of the UAV'"'"'s and is configured so that each UAV communicates with its closest neighbors only, and control information comprising flocking data propagates from node to node using a tree management or hierarchical protocol; (ii) wireless ad-hoc communications means between the UAV'"'"'s as follows;
for communicating attack target list and flocking information both from the root downstream towards other nodes in the sub-trees and from each node upstream towards the root;
the root node gathers task assignment and flocking data calculated by its sub-trees, calculates global functions, task assignment and flocking data for the tree;
the root node distributes said global functions, task assignment and flocking data back to its sub-trees;
in conditions where communication between the UAV'"'"'s is constantly disrupted due to dynamic changes in the field, the constant flow of upstream and downstream data improves the overall efficiency of the UAV'"'"'s in the tree; and(iii) task assignment means configured so that each UAV, using a graph-theoretic approach, locates all detectable attack targets;
identifies said attack targets;
computes the distance to each of said attack targets; and
produces an attack plan based on system parameters, such that said attack plan optimizes the distances between said UAV'"'"'s to said attack targets. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A hierarchical multiple Unmanned Aerial Vehicle (UAV) decision and control system comprising flocking means based on a behavioral heuristic algorithm wherein said algorithm controls the velocity and heading of the UAV'"'"'s and is configured so that each UAV communicates with its closest neighbors only, and control information comprising flocking data propagates from node to node using a tree management or hierarchical protocol.
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21. A hierarchical multiple UAV decision and control system comprising task assignment capabilities wherein each UAV, using a graph-theoretic approach, locates all detectable attack targets;
- identifies said attack targets;
computes the distance to each of said attack targets; and
produces an attack plan based on system parameters, such that said attack plan optimizes the distances between said UAV'"'"'s to said attack targets.
- identifies said attack targets;
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22. A wireless ad-hoc communications method for communicating between multiple UAV'"'"'s organized in a hierarchical decision tree structure, the method comprising the steps of:
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(i) communicating attack target list and flocking information both from the root downstream towards other nodes in the sub-trees and from each node upstream towards the root; (ii) gathering by the root node task assignment and flocking data calculated by its sub-trees, calculating global functions, task assignment and flocking data for the tree; and (iii) distributing by the root node said global functions, task assignment and flocking data back to its sub-trees.
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Specification