UAV Hazard Source Mapping Algorithm for Radiation Localization
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Solution Overview
Problem
Current technologies lack a rigorous reconstruction algorithm for the spatial distribution of contaminant sources, particularly in emergency response scenarios like nuclear or radiological accidents, and for environmental contaminants like hazardous chemicals. Additionally, there is a need for efficient mapping and adaptive data collection systems to quickly locate and quantify radiation sources and other environmental substances.
Innovation Solution
The proposed solution involves developing a scalable and robust source-mapping algorithm that uses deconvolution and reconstruction methods to estimate the unknown spatial distribution of radiation sources. This algorithm can be applied to various platforms, including UAVs, trucks, and robots, and can adapt to different types of environmental contaminants. The method involves classifying the radiation mapping inverse problem and applying Maximum a Posteriori (MAP) and least square (LS) solutions to solve the convolution and reconstruction problem.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional detection methods are used to locate radiation sources, then ground personnel can identify contaminants, but the dose exposure to ground personnel increases and response time is delayed
Solution Approach 1:
The patent introduces an unmanned aerial vehicle (UAV) as an intermediary carrier to host the radiation detector. The UAV flies autonomously through the contaminated environment, collecting radiation data without exposing ground personnel to harmful radiation. This mediator approach allows remote sensing of radiation sources while protecting human operators from dose exposure.
Solution Approach 2:
The patent replaces manual ground-based detection with an automated aerial system. The UAV is equipped with radiation detectors and implements autonomous navigation algorithms to search for and locate radiation sources. This substitution of mechanical/manual operations with automated aerial systems eliminates human exposure risks while improving detection efficiency.
2Loss of information
If comprehensive radiation mapping is performed to identify all sources, then complete environmental assessment is achieved, but the time and computational resources required increase significantly
Solution Approach 1:
The patent implements a two-stage detection approach. First, a rapid survey phase collects coarse radiation data to identify regions of interest. Second, a detailed mapping phase focuses computational resources only on areas with detected anomalies. This preliminary screening action prevents unnecessary comprehensive mapping of entire regions, reducing time and computational resource consumption while maintaining information completeness for relevant areas.
Solution Approach 2:
The patent divides the radiation mapping task into discrete spatial zones or regions of interest. Instead of processing the entire environment uniformly, the system segments the search space and applies targeted detection algorithms to each segment. This segmentation allows parallel processing and focuses computational resources on areas with highest probability of containing radiation sources, reducing overall mapping time.
3Measurement precision
If multiple detectors are deployed to improve source localization accuracy, then measurement precision increases, but device complexity and cost increase
Solution Approach 1:
The patent transitions from ground-based planar detection to three-dimensional aerial detection. By positioning the detector in the air space above the environment, the system gains additional spatial dimension for source localization. This dimensional change allows accurate source identification using fewer detectors, as the vertical perspective provides geometric advantages for triangulation and spatial reconstruction without requiring dense detector arrays.
Solution Approach 2:
The patent designs a multi-functional UAV platform that integrates radiation detection, navigation, communication, and autonomous control systems. This universal platform performs multiple functions including source detection, spatial mapping, real-time data transmission, and adaptive path planning. By consolidating these functions into a single integrated system rather than separate devices, the overall system complexity is reduced while maintaining high measurement precision.
Data Source
AI summary
An image reconstruction algorithm system for hazardous source mapping. The algorithm system can be used to automate and optimize the search path of a movable vehicle (such as a UAV), equipped with detection capability. The algorithm allows the vehicle to localize hazardous sources in multiple scenarios effectively. Hazard mapping is formulated as an inverse problem and solved either with a deconvolution or a reconstruction algorithm, according to the problem complexity. The algorithms can use the Maximum a Posteriori (MAP) and the least square regression algorithm, respectively. However, alternative algorithms can be used as set forth herein. The source mapping algorithms are able to provide a quantitative estimation of the hazard source magnitude. A non-negative version of the least square algorithm is used to reconstruct the map at each step of the navigation algorithm of the vehicle. The navigation algorithm correctly located single and multiples simulated hazardous sources.