Autonomous Vehicle Explosive Field Mapping
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Solution Overview
Problem
Existing technologies lack an efficient method to detect and map explosive devices in fields, hindering safe human movement and land use, particularly in areas contaminated with landmines and unexploded ordnance, due to the need for comprehensive scanning of large areas.
Innovation Solution
A system utilizing autonomous vehicles equipped with sensors and data fusion technologies generates a map of suspicious areas by analyzing global, static, and dynamic data types, classifying zones as hazardous, suspected hazardous, or non-hazardous, and updates the map based on actual data from autonomous vehicles, allowing for targeted clearance efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive scanning of large areas is performed to detect explosive devices, then detection coverage is improved, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The system performs preliminary classification of areas into hazardous, suspected hazardous, and non-hazardous zones using multiple data sources (satellite imagery, historical conflict data, terrain analysis) before conducting detailed scanning. This preliminary action identifies high-probability areas for explosive devices, allowing resources to be concentrated where they are most needed rather than scanning entire regions uniformly.
Solution Approach 2:
The large contaminated area is segmented into distinct zones based on risk levels: hazardous areas requiring immediate detailed scanning, suspected hazardous areas for moderate scanning, and non-hazardous areas for minimal or no scanning. This segmentation enables differential allocation of scanning resources, improving overall detection efficiency while maintaining coverage of critical areas.
2Measurement precision
If comprehensive scanning of large areas is performed to detect explosive devices, then detection accuracy is improved, but resource consumption deteriorates
Solution Approach 1:
Different scanning intensities and methods are applied to different regions based on their specific risk characteristics. Hazardous areas receive intensive multi-sensor scanning, suspected areas receive moderate scanning, and non-hazardous areas receive minimal scanning. This local differentiation optimizes resource consumption by concentrating resources where detection accuracy is most critical.
Solution Approach 2:
The system applies partial scanning actions to areas where full comprehensive scanning would be excessive resource consumption. By using preliminary classification to identify only the necessary portions of areas requiring detailed inspection, the system achieves adequate detection accuracy without the resource cost of scanning entire regions uniformly.
3Measurement precision
If autonomous vehicles with multiple sensors are deployed to collect actual data, then map accuracy is improved, but device complexity deteriorates
Solution Approach 1:
The autonomous vehicles are designed as multi-functional platforms that integrate multiple sensor types (magnetic sensors, ground-penetrating radar, visual sensors, hyperspectral cameras) and navigation systems into a single unified system. This multi-functionality allows one vehicle to perform various detection tasks across different environments, improving map accuracy through comprehensive data collection while avoiding the need for multiple specialized vehicles.
Solution Approach 2:
The system merges data from multiple independent sensor sources and integration methods into a unified explosive devices field map. By combining magnetic field data, radar imagery, visual observations, and hyperspectral analysis into a single integrated mapping system, the approach achieves high map accuracy while managing complexity through centralized data fusion rather than multiple separate systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the need for extensive scanning by focusing on high-probability areas, enhancing safety and efficiency in mine clearance operations, thereby facilitating human movement and land use rehabilitation.
Implementation Method 1
a hyperspectral camera to sense explosives based on a reflected emission from a ground surface
Implementation Method 2
a ground penetrating radar to provide data related to the explosive devices at the explosive devices field
Implementation Method 3
a magnetic field sensor to sense metals
Data Source
AI summary
A system and a method for generating a map of an explosive devices field is disclosed. The system includes a processing device which configured to generate the map by processing and learning data receive from one or more global databases and one or more local databases and from actual data collected from the explosive devices field by an autonomous vehicle (AV). The map includes locations of subspecies areas of explosive devices which updated by the AV.