Coordinated Drone Fleet Control for Collision-Safe Damage Surveys

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Solution Overview

Problem

Current methods for collecting data on property damage, such as those used in insurance claims, are time-consuming, inefficient, and prone to inaccuracies due to manual control and potential collisions among multiple drones, leading to extended claim resolution times.

Innovation Solution

A system comprising a fleet of autonomous or semi-autonomous drones communicatively coupled with a damage identification computing device that navigates a geographical region to detect damage, communicates to prevent collisions, and stores data in a blockchain structure for secure record-keeping, allowing for efficient and accurate damage assessment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If multiple drones are used to capture damage data, then the data collection coverage is improved, but the risk of collisions between drones increases

Engineering Contradiction:

Improvedata collection coverageVSAvoidcollision risk

Core Design Contradiction:

Area of stationary objectVSReliability

Solution Approach 1:

The system implements real-time feedback through continuous inter-drone communication, where each drone reports its position and the central controller adjusts flight paths dynamically to maintain safe separation distances while preserving comprehensive damage area coverage

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The drone fleet operates with dynamic, adaptive flight paths that are continuously adjusted based on real-time position data and collision risk assessments, allowing the system to optimize both coverage area and safety margins simultaneously

Inventive Principle:

Principle #15Dynamics

2Productivity

If multiple drones are deployed to collect damage data, then the productivity of data collection is improved, but the overlap between collected data increases

Engineering Contradiction:

Improvedata collection efficiencyVSAvoiddata overlap

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The damage assessment area is segmented into distinct zones assigned to individual drones, with each drone responsible for capturing data from specific angles and locations, ensuring comprehensive coverage while minimizing redundant overlap through systematic division of the inspection space

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Drones are positioned at different spatial dimensions (elevations, angles, and locations) to capture damage data from multiple perspectives simultaneously, increasing productivity while reducing overlap through three-dimensional spatial distribution of data collection points

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Device complexity

If a single drone is used to collect damage data, then the system complexity is reduced, but the time required for data collection increases

Engineering Contradiction:

Improvesystem complexityVSAvoiddata collection time

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

Multiple autonomous drones are merged into a coordinated fleet that operates under centralized control, combining their capabilities to simultaneously cover multiple areas and capture comprehensive damage data from various angles, thereby reducing total inspection time while maintaining manageable system complexity through integrated control architecture

Inventive Principle:

Principle #5Merging (Combining)

4Ease of operation

If manual control is used for drone navigation, then the ease of operation is improved, but the accuracy and speed of damage assessment deteriorates

Engineering Contradiction:

Improvedrone control simplicityVSAvoiddamage assessment accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

Drones are equipped with autonomous navigation and damage detection capabilities that enable self-service operation, where the system automatically performs navigation, data collection, and preliminary analysis without requiring continuous manual intervention, thereby achieving both operational simplicity and high assessment accuracy through embedded intelligence

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11430180B2Systems and methods for controlling a fleet of drones for data collection

Publication Date: 2022.08.30 STATE FARM MUTAL AUTOMOBILE INSURANCE COMPANY

AI summary

A damage identification (DI) system for identifying property damage may include a drone fleet including several autonomous or semi-autonomous drones communicatively coupled together and a DI computing device. Each drone may collect drone-collected damage data, including image data. The DI computing may assign a geographical region to the drone fleet. The drone fleet may automatically navigate to, and then within, the geographical region to detect potential damage to properties. The DI computing device may further receive drone-collected damage data associated with a property within the geographical region from the drone fleet when the drone fleet determines the property is actually or potentially damaged, generate aggregated damage data associated with the property based at least partially upon the drone-collected damage data, and/or store the aggregated damage data in a blockchain structure associated with the property for damage assessment of the property.