Robotic VIN And Image Capture for Vehicle Damage Attribution
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Solution Overview
Problem
Current methods for tracking vehicle damage in the supply chain are inefficient and prone to human error, leading to incorrect identification of responsible parties and increased costs due to inadequate inspection processes, particularly in tight spacing configurations.
Innovation Solution
A system utilizing autonomous robots equipped with cameras and GPS, capable of capturing high-quality images and VIN numbers, which communicate with a cloud-based software to associate images with vehicle records and locations, reducing the need for manual intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human inspectors manually inspect vehicles, then they can document damage with paperwork, but the inspection quality is insufficient and human error occurs
Solution Approach 1:
The patent replaces manual human inspection with an automated robotic inspection system equipped with cameras and image processing algorithms. The robot autonomously navigates to vehicles, captures images from multiple angles, and uses computer vision to detect and document damage, eliminating human error and inconsistency while improving detection accuracy and reliability.
Solution Approach 2:
The system creates accurate visual copies of vehicle conditions through high-resolution photography and 360-degree imaging. These digital copies serve as permanent records of vehicle condition at each supply chain stage, allowing objective comparison and damage attribution without relying on subjective human assessment.
2Extent of automation
If a drive through garage with cameras is used, then automated image capture is achieved, but the unloading process is significantly slowed down
Solution Approach 1:
The inspection system is designed to be dynamic and adaptable to the existing fast-paced unloading environment. The robot can quickly scan vehicles as they are being unloaded, capturing images without requiring vehicles to stop or enter a separate inspection facility, thus maintaining unloading speed while achieving automation.
Solution Approach 2:
The system performs preliminary automated documentation of vehicle conditions during the unloading process itself, rather than requiring a separate post-unloading inspection phase. This allows images to be captured in real-time as vehicles arrive, eliminating delays while maintaining automation.
3Productivity
If human inspectors are given 200 cars per day, then inspection throughput is maintained, but inspection quality deteriorates due to time pressure
Solution Approach 1:
The patent replaces human inspectors with an automated robotic system that can inspect vehicles at high speed without compromising quality. The robot captures comprehensive images and uses algorithmic analysis to detect damage, achieving both high throughput (exceeding 200 vehicles per day) and consistent detection quality without the fatigue and time pressure that affect human inspectors.
Solution Approach 2:
The automated system enables continuous inspection operations without breaks, maintaining consistent detection quality throughout the workday. Unlike human inspectors whose performance may deteriorate over time, the robot provides uninterrupted, consistent inspection capability at high volume.
4Area of stationary object
If tight spacing between vehicles is maintained, then storage efficiency is improved, but inspector positioning for good vantage points becomes difficult
Solution Approach 1:
The robotic inspection system overcomes tight spacing constraints by operating in three-dimensional space. The robot can position itself at optimal heights and angles around vehicles, using its mobile platform and articulated camera system to capture images from perspectives that would be inaccessible to human inspectors confined to ground level between tightly packed vehicles.
Solution Approach 2:
The patent replaces human inspectors with a mobile robotic system equipped with cameras and navigation capabilities. The robot autonomously positions itself around vehicles in tight spaces, capturing high-quality images from multiple angles without requiring the wide access spaces that human inspectors need for proper positioning and documentation.
Data Source
AI summary
A system for capturing VIN numbers and vehicles images to track vehicle damage through vehicle supply chains which includes a mobile software application and/or robot(s) which moves autonomously around parking lots. The mobile application can direct the user to capture VIN images and/or vehicle images from certain views and collect GPS positions of the same and the robot includes various cameras and sensors to identify vehicles and take pictures of them. All of the captured images of vehicles are sent to a central server/storage where the vehicle images can be checked for damage as compared to locations so that it can be determined who was in possession of the vehicle when damage occurred.