Industrial Robot Stiffness Modeling Across Variable Workspaces
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Solution Overview
Problem
Industrial robots have weak stiffness due to their series structure, leading to low tolerance for working loads, reduced machining accuracy, and poor cutting stability, making it difficult to meet the requirements of high-accuracy manufacturing and complex assembly processes.
Innovation Solution
A variable-parameter stiffness identification and modeling method that divides the robot's operating space into cubic grids, using a six-dimensional force sensor and laser tracker to measure load and deformation at multiple positions and postures, and establishing a stiffness model that accounts for nonlinear joint stiffness characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional stiffness identification methods are used, then the modeling process is simple, but the stiffness modeling accuracy is insufficient for high-precision machining requirements
Solution Approach 1:
The robot's operating space is divided into multiple cubic grids, with stiffness identification performed separately for each grid. This segmentation allows the system to capture spatial variations in stiffness characteristics while maintaining manageable complexity through localized measurements and modeling.
Solution Approach 2:
The patent implements variable-parameter stiffness identification that adapts to different robot postures and positions. By dynamically adjusting measurement and modeling parameters based on the current operating state, the system achieves high accuracy across the entire working space rather than relying on a single static model.
2Adaptability or versatility
If joint stiffness is identified under a single posture, then the measurement process is simple, but the applicability to the whole working space is poor
Solution Approach 1:
The working space is segmented into multiple cubic grids, and stiffness identification is performed for representative postures within each grid. This approach ensures coverage of the entire working space while reducing the total number of measurements needed compared to exhaustive sampling.
Solution Approach 2:
The patent identifies joint stiffness parameters in advance for multiple pre-defined postures and positions throughout the working space. These pre-identified parameters are stored and selected based on the robot's current state, enabling rapid application without real-time measurement delays.
3Measurement precision
If linear elastic relationship is assumed, then the modeling calculation is simple, but the nonlinear joint stiffness characteristics are not captured
Solution Approach 1:
The patent models joint stiffness as variable parameters that change with robot posture and position rather than assuming constant linear elastic properties. By allowing stiffness parameters to vary according to the robot's operating state, the model captures nonlinear characteristics while maintaining computational efficiency through parameterization.
Data Source
AI summary
Disclosed is a variable-parameter stiffness identification and modeling method for an industrial robot. An effective working space of a robot is divided into a plurality of cubic regions. For an operating task in a certain machining region, different loads are applied to an end effector at multiple positions and multiple postures in the region, and robot joint stiffness in this section is identified and acquired according to the relationship between the loads and an end deformation, thereby realizing accurate stiffness control of the robot in different operating sections during a machining process.