Wi-Fi Aware Drone Cluster Formation and Merging

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Solution Overview

Problem

Current solutions for drone cluster formation in wireless communication systems, such as those using IEEE 802.11 standards, lack efficient algorithms for determining and merging clusters, particularly in environments like drone navigation, leading to inefficiencies and increased power consumption.

Innovation Solution

The implementation of a modified Wi-Fi Aware protocol that enables cluster formation and merging based on specific information like flight paths and destination details, using techniques such as application-layer decisions, protocol stack layer operations, and hard-coded methods to manage cluster grades and merge drone clusters efficiently.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If traditional Wi-Fi protocols are used for drone cluster formation, then basic communication is achieved, but power consumption increases and cluster management efficiency decreases

Engineering Contradiction:

Improvepower consumptionVSAvoidcluster management efficiency

Core Design Contradiction:

Use of energy by moving objectVSProductivity

Solution Approach 1:

The patent modifies Wi-Fi protocol parameters specifically for drone clusters, changing transmission power levels, beacon intervals, and data rate settings to optimize for the specific requirements of drone communication. This allows reduced power consumption while maintaining cluster management efficiency through parameter optimization rather than complete protocol redesign.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent segments cluster management functions by designating specific drones as cluster heads that handle coordination tasks, while other drones focus on execution. This segmentation reduces overall power consumption by distributing management responsibilities and allowing non-head drones to enter low-power states more frequently.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If proprietary communication methods are used for drone clusters, then specialized functionality is achieved, but cost increases

Engineering Contradiction:

Improvespecialized functionalityVSAvoidcost

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

The patent makes existing Wi-Fi protocols multi-functional by configuring them to handle both standard wireless communication and specialized drone cluster formation tasks. This universality allows commercial off-the-shelf Wi-Fi hardware to perform specialized functions, eliminating the need for expensive proprietary communication systems while maintaining adaptability for drone-specific applications.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent creates virtual representations of cluster structures and communication patterns using standard Wi-Fi protocols, copying the essential functionality of proprietary systems through software-based implementations rather than hardware-specific solutions. This allows specialized drone cluster functionality to be achieved through configuration and algorithm design rather than custom hardware.

Inventive Principle:

Principle #26Copying

3Ease of operation

If cluster grade based merging is enabled by default, then cluster formation is simplified, but merging accuracy decreases

Engineering Contradiction:

Improvecluster formation simplicityVSAvoidmerging accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent implements dynamic cluster grade assignment where the grade is not fixed but adjusts based on real-time factors such as drone capabilities, current task requirements, and environmental conditions. This dynamic approach maintains ease of operation through automated grade management while improving merging accuracy by adapting grades to actual operational needs rather than using static predetermined values.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent incorporates feedback mechanisms where cluster merging outcomes are evaluated and used to adjust future merging decisions. The system learns from past merging accuracy and refines cluster grade assignments accordingly, maintaining operational simplicity through automated learning while progressively improving merging precision based on accumulated experience.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS10298674B2Enhancing Wi-Fi aware protocol and algorithms for drone cluster formation

Publication Date: 2019.05.21 INTEL CORP

AI summary

At least three different techniques are presented that facilitate cluster formation in clusterable devices such as drones. The techniques facilitate power saving in the individual clusterable devise as well as for the entirety of the cluster. The first technique utilizes a NAN application based cluster formation decision. The second technique initiates a cluster grade merging evaluation based on a “merge allowed” field in a synchronization beacon set by the discovery engine. The third technique involves a discovery engine managing cluster formation with pre-set cluster grade information.