Pre-screening Component for Robotic Object Recognition
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Solution Overview
Problem
Robotic devices face challenges in recognizing objects, particularly in dynamic environments like railyards, due to difficulties in distinguishing target components from false positives and maintaining real-time processing capabilities while moving, which leads to inefficiencies and potential damage.
Innovation Solution
A pre-screening component that uses cameras and a computer system to identify reference targets and locate relevant components of objects, providing pre-screening data for further processing, allowing robotic devices to perform operations autonomously or semi-autonomously with reduced computational load and increased accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a robotic device processes image data in real-time while moving through a dynamic environment, then it can respond to changing conditions, but it experiences computational overload and difficulty distinguishing target components from false positives
Solution Approach 1:
The system performs preliminary image processing and target identification before the robotic device reaches the operation location. A pre-screening component captures and processes images of the vehicle and its components in advance, identifying reference targets and their locations beforehand. This allows the robotic device to receive pre-processed data with identified targets already marked, reducing the computational burden during real-time operation while maintaining the ability to respond to dynamic conditions.
2Productivity
If a robotic device uses simple target characteristics for quick identification, then it achieves fast processing, but it generates many false positives
Solution Approach 1:
The image processing system divides the analysis into multiple segments or stages. First, it identifies simple geometric characteristics for quick screening. Then, it progressively applies more complex analysis to verify potential targets, examining multiple characteristics in sequence. This segmented approach allows the system to quickly filter out obvious non-targets while applying more rigorous verification only to promising candidates, thereby maintaining high processing speed while reducing false positives.
3Extent of automation
If a stationary pin-puller is used for railcars, then it can perform automated operations, but it cannot adapt to varying vehicle speeds and positions
Solution Approach 1:
The system transitions from a stationary, fixed-location pin-puller to a dynamic system that can adapt to varying conditions. The pre-screening component continuously captures images as vehicles pass through, and the system processes these images to determine the actual position and speed of each vehicle. Based on this real-time data, the robotic device adjusts its timing and positioning to perform operations on moving vehicles at various speeds and locations, providing both automation and adaptability.
Data Source
AI summary
A solution for pre-screening an object for further processing is provided. A pre-screening component can acquire image data of the object and process the image data to identify reference target(s) corresponding to the object, which are visible in the image data. Additionally, the pre-screening component can identify, using the reference target(s), the location of one or more components of the object. The pre-screening component can provide pre-screening data for use in further processing the object, which includes data corresponding to the set of reference targets and the location of the at least one component. A reference target can be, for example, an easily identifiable feature of the object and the component can be relevant for performing an operation on the object.