Robot Manipulator Kinematic Modeling From 3D Joint Image Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robot manipulators face challenges in adapting to on-site situations due to a lack of expertise and difficulty in constructing kinematic information.
Innovation Solution
An apparatus and method that utilize deep learning-based feature detection models to derive Denavit-Hartenberg (DH) parameters from image information, enabling the construction of kinematic information for robot manipulators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional methods are used to construct kinematic information of robot manipulators, then measurement precision and manufacturing precision are maintained, but device complexity and difficulty of operation increase due to requiring expert knowledge
Solution Approach 1:
The patent replaces manual expert-based kinematic construction with an automated image processing system. The apparatus captures images of the robot manipulator, automatically detects joint positions and types through image analysis, and constructs DH parameters without requiring expert mechanical knowledge, thus substituting complex manual procedures with automated computational methods
Solution Approach 2:
The patent creates a digital representation (copy) of the physical robot manipulator through image capture and processing. By constructing kinematic models from images rather than direct physical measurement, the system simplifies the construction process while maintaining accuracy, allowing users to work with digital copies instead of complex physical measurements
2Ease of operation
If automated image-based methods are used to construct kinematic information, then ease of operation improves and expert knowledge is not required, but measurement precision may be affected
Solution Approach 1:
The patent implements feedback mechanisms in the image processing system where detected joint positions and types are validated and refined through iterative analysis. The system processes images to extract kinematic parameters, verifies the results against expected ranges, and adjusts detections accordingly, ensuring measurement precision is maintained while keeping the operation automated and accessible
Solution Approach 2:
The patent transitions from three-dimensional physical measurement to two-dimensional image-based measurement, then compensates by using multiple views or depth information. This dimensional change simplifies the measurement process while maintaining precision through computational geometry and coordinate transformation algorithms that accurately reconstruct 3D joint positions from 2D image data
Data Source
AI summary
An apparatus for constructing kinematic information of a robot manipulator is provided. The apparatus includes: a robot image acquisition part for acquiring a robot image containing shape information and coordinate information of the robot manipulator; a feature detection part for detecting the type of each of a plurality of joints of the robot manipulator and the three-dimensional coordinates of the joint using a feature detection model generated through deep learning based on the robot image containing shape information and coordinate information; and a variable derivation part for deriving Denavit-Hartenberg (DH) parameters based on the type of each of the plurality of joints of the robot manipulator and the three-dimensional coordinates of the joint.