Inspection Target Deduplication in Cluster Drone Inspection
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Solution Overview
Problem
In cluster inspection scenarios, overlapping regions covered by multiple drones or inspection devices lead to repeated target statistics, resulting in statistical bias during inspection tasks.
Innovation Solution
A method and apparatus for detecting and positioning inspection targets, which involve obtaining a target inspection sub-region, detecting the first inspection target within that sub-region, deleting duplicate targets from the inspection target set, and displaying unique targets on an inspection map to prevent repeated statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple drones perform cluster inspection to cover larger areas, then inspection coverage and productivity are improved, but overlapping regions cause repeated target statistics and statistical bias
Solution Approach 1:
The inspection region is divided into distinct sub-regions assigned to different drones. Each drone is responsible for detecting targets within its assigned sub-region, preventing overlapping detection areas. This segmentation maintains comprehensive coverage while eliminating duplicate target statistics across the inspection zone.
Solution Approach 2:
A background server acts as an intermediary to manage target statistics from multiple drones. The server receives target detection data from each drone, identifies duplicate targets across different drones' data, and filters them out before final statistics are generated. This intermediary process ensures accurate target counting while maintaining the benefits of multi-drone inspection.
2Speed
If multiple inspection devices are used to increase inspection efficiency, then inspection speed is improved, but overlapping detection regions lead to repeated target counting
Solution Approach 1:
Target detection data from multiple inspection devices is merged into a unified target set. The system combines detection results from all devices and then applies deduplication logic to remove repeated targets. This merging approach maintains the high inspection speed provided by multiple devices while ensuring each target is counted only once in the final statistics.
Data Source
AI summary
The present disclosure provides a method and an apparatus for detecting and positioning an inspection target, a device, and a storage medium. The method includes: obtaining a target inspection sub-region of a target inspection device in a target inspection process, and detecting a first inspection target in the target inspection sub-region and a first geographical position of the first inspection target, where the target inspection process is a process in which a plurality of inspection devices perform inspection tasks in inspection regions; deleting a second inspection target and a geographical position of the second inspection target in an inspection target set, where the second inspection target is an inspection target that is in the inspection target set and that is located in the target inspection sub-region; adding the first inspection target and the first geographical position to the inspection target set; and displaying all inspection targets in the inspection target set at geographical positions corresponding to all the inspection targets in an inspection map. The technical solution can avoid repeated statistics of an inspection target in the inspection target set due to an overlapping region covered by the plurality of inspection devices.