Robot Motion Path Compensation Using Process Data Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for adjusting robot motion paths based on the difference between real and ideal shapes of rough products in manufacturing processes rely heavily on manual operations and fail to consider the impacts of various steps in the rough manufacturing procedure, leading to inefficiencies and defects in final products.
Innovation Solution
A method that involves obtaining process data from the first processing procedure, generating a predicted model for the product, and adjusting the robot motion path based on the model difference between the predicted and ideal shapes, allowing for real-time compensation of errors and feedback to improve subsequent processing procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual operations are used to measure the real shape and adjust the robot motion path, then the robot motion path can be adjusted based on the difference between real and ideal shapes, but the adjustment process becomes complex and time-consuming
Solution Approach 1:
The system performs preliminary measurement of the rough product's real shape before the robot processing step. By obtaining the real shape data in advance and comparing it with the ideal shape to generate a compensation value, the system prepares the shape correction information beforehand, enabling direct application during robot processing without time-consuming manual adjustments.
Solution Approach 2:
The system replaces manual measurement and adjustment operations with automated optical measurement devices and computer-controlled robot systems. The measurement device automatically captures the real shape, the computer calculates the compensation value by comparing real and ideal shapes, and the robot automatically applies the compensation to its motion path, eliminating manual intervention entirely.
2Manufacturing precision
If manual operations are used to adjust the robot motion path, then the robot can be adjusted based on real shape measurements, but the complexity of the adjustment process increases
Solution Approach 1:
The system merges the measurement device, computer processing, and robot control into an integrated automated system. The measurement device is directly connected to the computer, which automatically generates compensation values and transmits them to the robot controller. This unified system reduces operational complexity by eliminating separate manual steps for measurement, calculation, and adjustment.
Solution Approach 2:
The system enables self-service automation where the measurement device automatically captures real shape data, the computer autonomously calculates the compensation value by comparing real and ideal shapes, and the robot self-adjusts its motion path based on the generated compensation. This self-service mechanism eliminates the need for manual measurement and adjustment operations, reducing operational complexity.
3Productivity
If the robot motion path is predefined based on the ideal shape, then the robot processing can be simple and fast, but the final product cannot reach the expected shape and becomes defective
Solution Approach 1:
The system performs preliminary measurement of the rough product's real shape and generates a compensation value by comparing it with the ideal shape before the robot processing begins. This pre-prepared compensation information is then applied to adjust the robot motion path, allowing the robot to process the workpiece with shape corrections already built in, maintaining high processing speed while achieving accurate final shapes.
Solution Approach 2:
The system dynamically changes the robot motion path parameters by applying a compensation value to the predefined ideal motion path. The compensation value, calculated from the difference between real and ideal shapes, modifies the robot's position, speed, or trajectory parameters in real-time, enabling the robot to adapt to actual workpiece variations while maintaining efficient automated processing.
Data Source
AI summary
Embodiments of present disclosure relate to adjusting a robot motion path. In the method for adjusting a robot motion path, a first processing procedure may be performed on a first workpiece to obtain a first product. Then, first process data may be obtained, where the first process data describes an attribute of the first processing procedure for obtaining the first product from the first workpiece. Next, based on the obtained first process data, a robot motion path of a second processing procedure that is to be performed on the first product by a robot may be adjusted. Further, embodiments of present disclosure provide apparatuses, systems, and computer readable media for adjusting a robot motion path.