Autonomous VIN And Image Capture for Vehicle Damage Handoffs
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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 examine vehicles, then damage can be identified, but the inspection process is slow and prone to human error
Solution Approach 1:
The patent replaces manual human inspection with an automated robotic 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 damage, eliminating human error while maintaining high inspection speed.
Solution Approach 2:
The inspection system performs self-assessment through automated image capture and analysis. The robotic inspector independently identifies damage without requiring human intervention, and the system automatically documents findings with timestamped images and location data, enabling self-service damage detection throughout the supply chain.
2Measurement precision
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 patent employs a mobile robotic system that dynamically navigates to vehicles rather than requiring vehicles to pass through a fixed inspection structure. The robot can move independently through the facility, approaching vehicles from optimal angles and capturing images without interrupting the continuous flow of unloading operations.
Solution Approach 2:
The robotic system acts as an intermediary between the unloading process and damage detection. It operates independently in the background, autonomously approaching vehicles after they are unloaded, thereby decoupling the inspection function from the unloading timeline and eliminating delays.
3Quantity of substance
If tight spacing between vehicles is maintained, then storage efficiency is improved, but human inspectors cannot position themselves to get good vantage points
Solution Approach 1:
The patent replaces human inspectors with a robotic system that has superior positioning capabilities. The robot can navigate in tight spaces, extend arms with cameras to reach optimal viewing positions, and use articulated mechanisms to achieve vantage points that would be inaccessible to human inspectors in densely packed vehicle rows.
Solution Approach 2:
The robotic system accesses three-dimensional space around vehicles, using vertical movement and articulated arms to position cameras at multiple heights and angles. This dimensional flexibility allows the robot to capture images from perspectives that bypass the constraints of tight horizontal spacing between vehicles.
4Productivity
If multiple entities handle vehicles in the supply chain, then distribution efficiency is improved, but determining responsible parties for damage becomes difficult
Solution Approach 1:
The patent implements preliminary damage documentation at each transfer point in the supply chain. The robotic system captures baseline images when vehicles are received and subsequent images when transferred, creating a time-stamped visual record that proactively identifies damage location and assigns responsibility before vehicles change hands.
Solution Approach 2:
The system provides continuous feedback about vehicle condition throughout the supply chain by automatically documenting damage and transmitting location data to all relevant parties. This real-time information flow ensures that each entity receiving a vehicle has immediate knowledge of its condition and can be held accountable accordingly.
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.