Adaptive Robotic Machining Path Correction
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Solution Overview
Problem
Current robotic machining methods, such as manual and offline programming, face challenges in achieving optimal machining performance due to size deviations between ideal and actual workpieces, particularly with complex workpieces, leading to inefficiencies and reduced processing quality.
Innovation Solution
An intelligent robotic machining system that generates a machining path based on a modeled surface and optimizes it using real-time feedback from the robot, allowing for adaptive machining with controlled force and speed adjustments to align with the actual workpiece surface, thereby eliminating size deviations and improving processing quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If offline programming method is used to generate machining path from ideal workpiece model, then programming time is reduced, but size deviation between ideal model and actual workpiece occurs
Solution Approach 1:
The patent implements a feedback mechanism where the robot equips sensors to detect the actual workpiece surface in real-time during machining. The control system receives feedback signals from these sensors about the actual surface geometry and dynamically adjusts the machining path accordingly. This closed-loop feedback eliminates size deviations by continuously adapting to the actual workpiece dimensions, resolving the contradiction between fast programming and high precision.
Solution Approach 2:
The patent transitions from static pre-programmed machining paths to dynamic, real-time adaptive paths. The control system dynamically modifies the machining trajectory based on real-time sensor feedback about the actual workpiece surface. This dynamic adjustment capability allows the system to compensate for size deviations between ideal models and actual workpieces while maintaining efficient machining speeds.
2Manufacturing precision
If manual programming method is used to handle complex workpieces, then machining path accuracy is improved, but processing time increases significantly
Solution Approach 1:
For complex workpieces, the patent employs real-time feedback from sensors that detect the actual surface geometry during machining. This feedback mechanism automatically adjusts the machining path to maintain high accuracy without requiring manual programming. The system learns the complex surface topology through sensor data and adapts the toolpath dynamically, achieving both high precision and reduced processing time compared to manual programming.
Solution Approach 2:
The system performs self-adjustment by automatically detecting workpiece features through sensors and generating appropriate machining paths without human intervention. The control system processes sensor feedback and autonomously modifies the toolpath to handle complex geometries, eliminating the time-consuming manual programming process while maintaining the accuracy that would otherwise require expert manual programming.
3Extent of automation
If fore control technology is used for complex workpieces, then machining automation is improved, but programming complexity and processing time increase
Solution Approach 1:
The patent simplifies automation programming by implementing intuitive sensor-based feedback control. Instead of complex fore control programming, the system uses straightforward sensor feedback to automatically detect workpiece surfaces and adjust machining paths in real-time. This feedback approach achieves high automation levels while keeping the control logic simple and easy to implement, avoiding the programming complexity associated with traditional fore control methods.
Data Source
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AI summary
A method for robotic machining is disclosed. The method includes determining a first designed machining path based on a modeled surface for a target surface to be machined (210). The method also includes causing a robot to machine the target surface based on the first designed machining path in an adaptive manner to obtain an actual machining path, wherein where the modeled surface is different from the target surface, the robot is caused to follow the target surface (220). The method further includes determining a second designed machining path for the target surface based on the actual machining path and the first designed machining path (230).