Autonomous Vehicle Image Filtering for Cooperative Object Search
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Solution Overview
Problem
Conventional methods for finding missing pets are inefficient, relying on manual searches and preregistering unique traits in databases, which can be time-consuming and limited in scope.
Innovation Solution
A system utilizing autonomous vehicles to passively search for specific objects by filtering images based on user-provided characteristics, allowing multiple vehicles to cooperatively scan large areas for the object and transmit relevant images to the user for identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual searching methods are used to find missing pets, then the search process can be performed with simple equipment, but the search efficiency and area coverage are limited
Solution Approach 1:
The autonomous vehicle system performs multiple functions: it conducts object searches, captures images, transmits data, and navigates autonomously. This multi-functional approach replaces multiple separate tools (manual search, cameras, databases) with a single integrated system, thereby improving search efficiency without proportionally increasing system complexity
Solution Approach 2:
The autonomous vehicles operate independently to perform search tasks. They autonomously navigate, capture images of potential objects, and transmit data without requiring continuous human intervention. This self-service capability significantly improves search productivity while keeping the operational complexity manageable
2Measurement precision
If a database system with unique traits is used to identify pets, then identification can be performed, but the process is time-consuming and requires third-party involvement
Solution Approach 1:
The system pre-registers objects in the environment with their unique characteristics before the search begins. When a search is initiated, the autonomous vehicles can immediately compare captured images against the pre-established database, eliminating the need for time-consuming on-site identification processes and reducing overall search time while maintaining identification accuracy
Solution Approach 2:
The manual process of third-party identification is replaced with an automated image recognition and comparison system. The autonomous vehicles capture images and the system automatically compares them against the database using computational algorithms, substituting the mechanical/manual identification process with an automated electronic system that operates faster and with consistent accuracy
3Area of stationary object
If autonomous vehicles are deployed to search for objects, then the search area coverage and efficiency are improved, but the system complexity and image filtering requirements increase
Solution Approach 1:
The image processing task is divided into multiple stages: initial filtering by the autonomous vehicle based on basic characteristics, followed by more detailed analysis and comparison by the central system. This segmentation of the image processing workload allows the autonomous vehicles to cover large areas efficiently while managing the complexity of image analysis through distributed processing
Solution Approach 2:
The central computing system acts as an intermediary between the autonomous vehicles and the final identification result. It receives images from multiple vehicles, performs centralized filtering and comparison against the database, and manages the overall search coordination. This intermediary role helps manage system complexity by centralizing the most computationally intensive tasks
Data Source
AI summary
A computing system that can receive an object search request from a user indicating a request to search for a specific object in an area traversed by one or more autonomous vehicle. The object search request can include a set of physical characteristics of the specific object. The computing system can then transmit a signal to an autonomous vehicle indicating a request for the autonomous vehicle to search for the specific object. The signal can cause the autonomous vehicle to transmit an image, selected based on a physical characteristic of the object, to the computing system. The computing system can then generate a score indicative of a difference between one or more physical characteristic of the object in the image and the specific object. The computing system can then selectively transmit the image to a mobile device operated by the user based on the score.