Shape Detection System with Dynamic Algorithm Selection
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Solution Overview
Problem
Existing systems for detecting the three-dimensional shapes of workpieces in a container are inefficient in accurately and quickly identifying objects with varying shapes and orientations, especially when they are randomly arranged.
Innovation Solution
A shape detection system comprising a distance image sensor, a sensor controller, and a user controller that uses a preset algorithm to detect and calculate the positions and orientations of workpieces, allowing for the creation and execution of customized recognition algorithms based on shape patterns and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed detection algorithm is used for all workpiece shapes, then the system structure is simple, but the detection accuracy and speed for various shapes deteriorates
Solution Approach 1:
The system allows dynamic selection and creation of detection algorithms based on workpiece shape characteristics. Users can choose from preset algorithms or create custom algorithms through the user controller, making the system adaptable to different shapes without requiring a completely different system for each shape type.
Solution Approach 2:
The system changes detection parameters by selecting different algorithms based on workpiece characteristics. The sensor controller can switch between various detection algorithms (e.g., for cylindrical, rectangular, or irregular shapes) by changing algorithm parameters, allowing accurate detection across different shapes using the same hardware.
2Measurement precision
If multiple detection algorithms are provided for different shapes, then the detection accuracy for specific shapes improves, but the system complexity and algorithm management difficulty increases
Solution Approach 1:
The user controller enables users to create and manage their own detection algorithms without system complexity interfering. Users can input shape characteristics and have the system generate appropriate algorithms automatically, making algorithm management user-friendly and reducing the burden on system complexity.
Solution Approach 2:
The system segments algorithm management into separate categories (preset algorithms and user-created algorithms). The sensor controller manages preset algorithms while the user controller handles custom algorithm creation, dividing the complex task of algorithm management into manageable segments.
3Productivity
If customized algorithms are created for each workpiece type, then the detection speed and accuracy for that type improves, but the time required for algorithm setup increases
Solution Approach 1:
The system provides preset algorithms that have been pre-created and optimized for common workpiece shapes. Users can immediately use these preset algorithms without spending time on setup, achieving fast detection for standard shapes. Custom algorithms can be created quickly using the user controller's template-based approach.
Solution Approach 2:
The system allows quick adjustment of algorithm parameters for different workpiece types without requiring complete algorithm recreation. Users can modify key parameters (dimensions, shapes) of existing algorithms to adapt them to new workpieces, reducing setup time while maintaining detection speed.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables quick and accurate detection of three-dimensional shapes of workpieces with various shapes, allowing for efficient operation of robots in picking and conveying tasks, and facilitates easy adaptation to new shapes and environments by allowing users to select and create algorithms suitable for specific conditions.
Implementation Method 1
a distance image sensor that detects an image of a plurality of detection objects and distances to the detection objects
Data Source
AI summary
A shape detection system includes a distance image sensor that detects an image of a plurality of detection objects and distances to the detection objects, the detection objects being randomly arranged in a container, a sensor controller that detects a position and an orientation of each of the detection objects in the container on the basis of the result of the detection performed by the distance image sensor and a preset algorithm, and a user controller that selects the algorithm to be used by the sensor controller and sets the algorithm for the sensor controller.