Robot Learning Path Control for Cutting Accuracy
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Solution Overview
Problem
Existing robotic cutting tool systems rely on manual teaching and iterative correction methods, which are time-consuming and limited in flexibility, and often result in undesirable cutting operations due to inaccuracies and material deviations during cutting processes.
Innovation Solution
A method that involves generating and displaying traces of actual tool center point positions to allow users to visually select and adjust programmed paths, enabling compensation and optimization of cutting paths based on subjective and objective criteria, without requiring extensive reprogramming or additional equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual teaching and iterative correction methods are used to program robot cutting paths, then the robot can be taught coordinate points and motions, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical teaching operations with automated optical scanning. A scanner captures images of the workpiece, and image processing algorithms automatically extract geometric features and generate robot path data, eliminating the need for manual coordinate teaching while maintaining high precision.
Solution Approach 2:
The patent introduces an intermediary system consisting of a scanner and image processing software between the workpiece and the robot controller. This intermediary automatically extracts geometric information and generates motion paths, serving as a bridge that converts visual data into robotic control commands without manual intervention.
2Manufacturing precision
If external sensors are added to track robot path and provide feedback for correction, then path accuracy can be improved, but system cost and complexity increase
Solution Approach 1:
The patent creates a digital copy of the workpiece geometry through optical scanning and image processing. This digital model is then used to generate and verify robot motion paths, providing accurate path prediction and correction without requiring additional physical sensors on the robot system.
Solution Approach 2:
The patent transitions from physical measurement to digital visualization by capturing the workpiece in 2D images and processing them into 3D geometric models. This dimensional transformation allows path verification and optimization in the digital domain before robotic execution, avoiding physical sensor complexity.
3Manufacturing precision
If command parameters such as acceleration and deceleration profiles are adjusted to correct robot path, then path accuracy can be improved, but flexibility is limited because corrections can only be made along the programmed curve
Solution Approach 1:
The patent implements dynamic path adjustment by allowing real-time modification of the digital model based on visual feedback. The system can dynamically recalculate optimal paths considering actual workpiece geometry variations, providing flexible corrections that are not constrained by the original programmed curve parameters.
4Manufacturing precision
If closed loop servo control with substantial data storage and buffering is implemented to monitor and adjust servo commands, then path accuracy can be improved, but data volume becomes sensitive to model and may produce negative results
Solution Approach 1:
The patent extracts only the essential geometric features and path parameters from the complete workpiece model. By focusing on critical dimensions and features relevant to cutting operations, the system reduces data storage requirements while maintaining the precision needed for accurate path control.
Data Source
AI summary
A robot is moved along a first continuous programmed path with a robot controller executing a learning path control program without performing an operation on a workpiece. The actual movement of the robot along the first continuous programmed path is recorded. The first continuous programmed path is adjusted to create a second programmed path. The robot is moved along the second continuous programmed with the robot controller executing the learning path control program without performing the operation on the workpiece. The actual movement of the robot along the second continuous programmed path is recorded. Traces of the recorded actual movements of the robot along the first continuous programmed path and the second continuous programmed path are displayed.