Robotic Object Detection With Minimum Viable Region Registration
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Solution Overview
Problem
Current robotic systems face challenges in efficiently and accurately detecting and handling unknown or unrecognized objects, leading to potential mishandling and increased operational disruptions, especially when objects are heavy or irregularly shaped, as they rely on pre-registered data and may fail to correctly identify physical characteristics.
Innovation Solution
A robotic system equipped with autonomous object detection and registration mechanisms that utilize image processing and sensor data to identify exposed edges and corners of unrecognized objects, derive minimum viable regions for gripping, and update registration data autonomously, allowing for the registration and handling of previously unknown objects without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robotic system relies on pre-registered data for object detection, then the system complexity is reduced and operation is simpler, but the system fails to correctly identify physical characteristics of unrecognized objects leading to mishandling
Solution Approach 1:
The system performs preliminary actions by capturing images of objects before handling operations. The imaging device captures images of the stack of packages, and the system processes these images to identify physical characteristics such as dimensions, weight, and center of mass. This preliminary detection allows the robotic system to adapt to unrecognized objects by establishing their characteristics before manipulation occurs.
Solution Approach 2:
The system implements feedback mechanisms by comparing captured images with registered images stored in a registration data source. When mismatches are detected, the system uses this feedback to trigger manual registration or to identify that an object is unrecognized, thereby adjusting its handling approach. The feedback loop ensures continuous improvement of detection accuracy for both recognized and unrecognized objects.
2Measurement precision
If manual registration of packages is performed, then detection accuracy for unrecognized objects is improved, but operational time increases and productivity decreases
Solution Approach 1:
The robotic system performs self-service by autonomously detecting and registering objects without requiring constant manual intervention. The system captures images, processes them to identify physical characteristics, and updates registration data automatically. This self-service capability reduces the need for manual registration while maintaining high detection accuracy, thereby preserving productivity.
Solution Approach 2:
The system replaces manual mechanical registration with automated image processing and computer vision techniques. Instead of relying on human workers to physically measure and register objects, the imaging device captures visual data, and the system automatically extracts physical characteristics such as dimensions, weight, and center of mass through image analysis algorithms.
3Speed
If the robotic arm handles heavy or lop-sided packages without accurate detection, then operational speed is maintained, but the risk of mishandling and bodily injuries increases
Solution Approach 1:
The system performs preliminary detection of physical characteristics including weight and center of mass before the robotic arm grasps and moves heavy packages. By identifying these characteristics in advance through image processing, the system can plan appropriate gripping strategies and motion paths, ensuring safe handling of heavy or lop-sided objects while maintaining operational speed.
Solution Approach 2:
The system uses feedback from image processing to continuously monitor and adjust handling parameters for heavy objects. When objects are detected as heavy or having unusual center of mass distribution, the feedback triggers adjustments in gripping force, arm positioning, and motion control to prevent mishandling while maintaining efficient operation.
Data Source
AI summary
A system and method for operating a robotic system to register unrecognized objects is disclosed. The robotic system may use first image data representative of an unrecognized object located at a start location to derive an initial minimum viable region (MVR) and to implement operations for initially displacing the unrecognized object. The robotic system may analyze second image data representative of the unrecognized object after the initial displacement operations to detect a condition representative of an accuracy of the initial MVR. The robotic system may register the initial MVR or an adjustment thereof based on the detected condition.