Autonomous Hazard Mapping for GPS-Denied Damage Assessment
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Solution Overview
Problem
Damage analysis in potentially hazardous locations is labor-intensive, dangerous, and prone to errors, with existing solutions like UAVs being expensive and limited in enclosed or low-visibility areas, and hazmat suits being costly and restrictive.
Innovation Solution
Autonomous vehicles equipped with AI logic modules capture data and generate 3-D maps to assess damage, navigating without GPS or remote control, reducing costs and improving safety by autonomously exploring hazardous areas and transmitting data to a base station.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remotely operated UAV devices are used for hazardous area investigation, then personnel safety is improved, but operational capability in closed spaces and low-visibility conditions deteriorates
Solution Approach 1:
The patent replaces GPS-based mechanical navigation with visual odometry and SLAM (Simultaneous Localization and Mapping) algorithms that use camera data to determine position and map the environment. This substitution enables autonomous navigation in GPS-denied environments like closed spaces and areas with smoke or low visibility, while maintaining personnel safety through remote operation.
Solution Approach 2:
The UAV performs self-navigation and self-mapping through autonomous flight control that uses onboard sensors and algorithms to navigate without human intervention. The system independently maps the environment, tracks its position, and returns to the launch point automatically, eliminating the need for continuous remote piloting and enabling operation in challenging conditions.
2Productivity
If commercially available UAV devices are used for damage analysis, then productivity is improved, but cost increases
Solution Approach 1:
The patent employs inexpensive, commercially available UAV devices (such as DJI Phantom models) that can be readily replaced if needed, rather than expensive specialized systems. The use of open-source software frameworks like ROS and standard computer vision libraries further reduces costs, achieving high productivity through damage analysis while maintaining cost-effectiveness.
Solution Approach 2:
The system uses multi-functional UAV platforms that can perform various tasks including visual inspection, thermal imaging, LiDAR scanning, and data transmission. This universality allows a single device to handle multiple investigation requirements, improving productivity while avoiding the need for multiple specialized expensive devices.
3Measurement precision
If hazardous material suits are used for area assessment, then measurement capability is improved, but ease of operation deteriorates
Solution Approach 1:
The system creates detailed digital 3D models and visual replicas of the hazardous area using photogrammetry and LiDAR data captured by the UAV. These digital copies allow for precise damage assessment and analysis without requiring personnel to physically enter the hazardous zone, thereby maintaining measurement precision while completely eliminating the operational limitations of hazmat suits.
Solution Approach 2:
The patent replaces human operators in hazmat suits with autonomous UAV systems equipped with multiple sensors (cameras, thermal imaging, LiDAR). This substitution maintains or enhances measurement precision through advanced sensing capabilities while completely eliminating the dexterity and movement restrictions imposed by hazardous material protective equipment.
Data Source
AI summary
Systems and methods for automatically identifying and ascertaining an estimated amount of damage at a location by utilizing one or more autonomous vehicles, e.g., “drone” devices, to autonomously capture data of the location and utilizing Artificial Intelligence (AI) logic modules to analyze the captured data and construct a 3-D model of the location.