Swarm Geolocation Control Using Local Voronoi Coordination
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Solution Overview
Problem
Conventional methods for geolocation of an acoustic source in a swarm of autonomous entities require synchronization among sensors, global coordination, and a leader entity, leading to computational overhead, inefficiency in mobile and dynamic conditions, and lack of fault tolerance.
Innovation Solution
A method where autonomous entities within the swarm independently send and receive sensory information to near neighbors, using game theory and biologically inspired algorithms to estimate the emitter source's location without a central controller, allowing for decentralized computation and movement decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all sensors are connected to share sensory information and generate Voronoi tessellation, then geolocation accuracy is improved, but computational speed decreases significantly
Solution Approach 1:
The patent divides the swarm into multiple Voronoi regions, with each entity independently computing its own region based on local sensory information from nearby entities. This segmentation eliminates the need for global information sharing while maintaining geolocation accuracy through distributed computation of local Voronoi cells.
Solution Approach 2:
Each autonomous entity computes Voronoi tessellation using only local sensory information from its immediate neighbors rather than global information from all entities. This local computation approach maintains measurement precision for local region identification while dramatically improving computational speed by avoiding centralized processing of all sensor data.
2Ease of operation
If a leader entity is selected to pinpoint the acoustic source location, then geolocation coordination is improved, but communication overhead increases significantly
Solution Approach 1:
The patent removes the leader entity from the system entirely, replacing centralized coordination with decentralized autonomous decision-making. Each entity independently determines its role and actions based on local Voronoi region computation, eliminating the communication overhead associated with leader selection and maintenance while preserving geolocation coordination capability.
Solution Approach 2:
Each autonomous entity autonomously computes its own Voronoi region and determines its own actions for geolocation without requiring coordination with a leader entity. This self-service approach eliminates communication overhead for leader selection while maintaining effective geolocation through independent local decision-making based on sensory information from nearby entities.
3Adaptability or versatility
If nodes or emitter source move requiring new leader selection, then adaptability to dynamic conditions is improved, but computational overhead worsens
Solution Approach 1:
The patent implements dynamic Voronoi region computation where each entity continuously updates its local region based on current positions of nearby entities and the emitter source. This dynamic local computation provides adaptability to moving nodes and sources without the computational overhead of periodic leader reselection, as each entity independently adapts to changing conditions in its local neighborhood.
4Productivity
If a central controller directs swarm members, then coordination efficiency is improved, but system reliability decreases due to single point of failure
Solution Approach 1:
The patent segments the centralized control function into distributed autonomous decision-making at each entity. Each entity independently computes its Voronoi region and determines its actions, eliminating the single point of failure while maintaining coordination efficiency through local information exchange and independent Voronoi-based decision-making.
Solution Approach 2:
Each entity autonomously determines its own actions for geolocation based on local Voronoi region computation without requiring directives from a central controller. This self-service approach eliminates the central controller as a single point of failure while maintaining coordination efficiency through independent local decision-making based on sensory information from nearby entities.
5Ease of operation
If swarm entities operate in synchronized manner with global communication, then coordination is improved, but area coverage decreases due to crowding
Solution Approach 1:
The patent segments the swarm into multiple independent Voronoi regions, with each entity operating autonomously within its local region based on nearby entities rather than synchronized global coordination. This segmentation reduces crowding by distributing entities across different local regions determined by Voronoi tessellation, thereby improving area coverage while maintaining coordination through local information exchange.
Data Source
AI summary
A method that pertains to location of an emitter source is provided. The method can use game theory and an estimation method. The method can use an autonomous entity that can operate independently of an external controlling entity, and independently of any other autonomous entity in a swarm of autonomous entities. A system comprising a swarm of autonomous entities and a control unit that can implement the method is provided.