Cooperative Net Capture of Maneuvering UAV Swarms in 3D
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Solution Overview
Problem
Current technologies lack effective methods for a team of UAVs to capture and surround a swarm of intruder UAVs, especially when the intruder swarm is maneuvering or changing size, posing a threat to protected airspace.
Innovation Solution
The development of cooperative pursuit guidance laws using collision cones, which enable UAVs to maneuver and orient a net to intercept and surround a swarm of intruder UAVs, even when the swarm is maneuvering or changing size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a team of UAVs uses traditional point-to-point interception methods, then the interception of single targets may be achieved, but the system cannot effectively capture maneuvering swarms of intruder UAVs
Solution Approach 1:
The swarm of intruder UAVs is segmented into individual targets, with each defense UAV assigned to intercept specific intruders. The collision cone concept is applied to each individual interception event, dividing the spatial environment into safe and dangerous regions for each target, enabling the defense team to systematically handle multiple maneuvering targets simultaneously
Solution Approach 2:
The interception problem is extended from traditional 2D plane to 3D space by incorporating vertical dimension. The collision cone concept is formulated in 3D space, allowing defense UAVs to intercept intruders from above or below, not just from the horizontal plane, thereby increasing interception effectiveness against maneuvering swarms
2Reliability
If the net is manipulated to pursue and orient toward maneuvering intruders, then capture effectiveness is improved, but the guidance system complexity increases
Solution Approach 1:
The guidance system continuously monitors the relative positions and velocities of defense UAVs and intruder swarms, updating collision cone calculations in real-time. This feedback mechanism allows the system to adapt to intruder maneuvers dynamically while maintaining structured control logic based on the collision cone framework
Solution Approach 2:
The collision cone is pre-calculated based on current relative motion states, providing advance guidance on safe and dangerous directions before actual interception occurs. This preliminary analysis of potential collision paths enables the guidance system to plan interception trajectories in advance, reducing real-time computational complexity
Data Source
AI summary
The present disclosure addresses the problem of UAVs pursuing a swarm of target UAVs. The target UAVs are flying together as a flock that are initially modeled as a circle having a time-varying radius or an arbitrarily-shaped swarm that may change in size. Guidance of the pursuing UAVs is developed based on a collision cone framework, wherein the pursuing UAVs cooperatively steer the velocity vector of any point in their convex hull, to intercept the target. Also, the problem of capturing a swarm of intruder UAVs using a net manipulated by a team of defense UAVs is disclosed. The intruder UAV swarm may be stationary, in motion, and even maneuver. Collision cones in 3-dimensional space are used to determine the strategy used by the net carrying UAVs to maneuver or manipulate the net in space in order to capture the intruders.