Automated Package Registration With Verified Grip Region Detection
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Solution Overview
Problem
Current robotic systems face challenges in efficiently registering and handling packages, particularly when physical characteristics such as dimensions and weight are unknown, leading to potential mishandling and increased risk of injury to human workers during de-palletization.
Innovation Solution
A robotic system that utilizes imaging sensors to identify exposed edges and corners of packages, generates Minimum Viable Regions (MVRs) to accurately grasp and manipulate unrecognized objects, and processes point cloud data to determine accurate grip locations, enabling autonomous registration and handling of packages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If packages are de-palletized by human workers, then flexibility and adaptability are maintained, but resource consumption increases and injury risk rises
Solution Approach 1:
The system enables autonomous package registration and handling through automated imaging, processing, and robotic manipulation. The robotic system independently identifies packages, determines their physical characteristics from images, and executes de-palletization without human intervention, making the system self-sufficient while reducing resource consumption and safety risks
Solution Approach 2:
The patent replaces human manual operations with an integrated system combining imaging devices, processing units, and robotic manipulators. The robotic arm with gripper substitutes human hands for gripping and moving packages, while the automated image processing replaces human visual inspection and decision-making, achieving both automation and adaptability
2Measurement precision
If physical characteristics of packages are unknown, then registration efficiency is reduced, but manual intervention can provide accurate information
Solution Approach 1:
The system performs preliminary imaging and processing of packages before actual handling operations. By capturing images and determining physical characteristics in advance, the system prepares accurate registration data beforehand, enabling both precise measurement and efficient subsequent robotic manipulation without manual intervention
Solution Approach 2:
The imaging device and processing unit serve as intermediaries between the robotic system and the packages. These components extract physical characteristics from visual data, translating package features into actionable information that guides robotic handling, thereby achieving both accuracy and efficiency without direct human measurement
3Productivity
If automated robotic systems are implemented, then productivity and safety are improved, but system complexity increases
Solution Approach 1:
The robotic system integrates multiple functions into a unified platform: imaging devices for detection, processing units for analysis, and robotic manipulators for execution. This multi-functional integration achieves high productivity while managing complexity through coordinated operation of standardized components rather than separate specialized systems
Solution Approach 2:
The system employs closed-loop feedback where imaging devices continuously monitor package positions and characteristics, processing units analyze the data, and robotic systems adjust their actions accordingly. This feedback mechanism enables accurate and efficient automated handling while managing complexity through adaptive control rather than overly sophisticated hardware
4Loss of time
If image matching with registered data is performed, then recognition speed is improved, but measurement precision deteriorates when no match is found
Solution Approach 1:
The system performs preliminary image matching against registered package data to quickly identify known packages. When matches are found, recognition is immediate. When no match is found, the system then performs detailed image processing to extract physical characteristics, ensuring both speed for recognized packages and accuracy for new packages
Solution Approach 2:
The system applies a two-level processing approach: first performing a quick partial check against registered data for rapid recognition, and only when necessary proceeding to full image processing for accurate measurement. This partial action strategy maintains high speed for common cases while ensuring precision when needed
Data Source
AI summary
The present disclosure relates to methods and systems for generating a verified minimum viable range (MVR) of an object. An exposed outer corner and exposed edges of an object may be identified by processing one or more image data. An initial MVR may be generated by identifying opposing parallel edges opposing the exposed edges. The initial MVR may be adjusted, and the adjusted result may be tested to generate a verified MVR.