Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP

Industrial robotic arms are often subject to significant end-effector pose deviations from the target position due to the combined effects of nonlinear deformations such as link flexibility, joint compliance, and end-effector load. To address this issue, a study was conducted on the analysis and com...

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Vydáno v:Sensors (Basel, Switzerland) Ročník 25; číslo 2; s. 378
Hlavní autoři: Xiang, Wenping, Chen, Junhua, Li, Hao, Chai, Zhiyuan, Lou, Yinghou
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 01.01.2025
MDPI
Témata:
Accuracy
Artificial intelligence
Automation
Calibration
Comparative analysis
Control
ECOA-BP neural network
Efficiency
error compensation
Flexibility
industrial robotic arm
Innovations
Kinematics
Manufacturing
Mathematical optimization
Methods
Neural networks
Product quality
rigid–flexible coupling
Robot arms
Robotics
Robots
Simulation
Systems stability
Technology application
China
ECOA-BP neural network
error compensation
industrial robotic arm
rigid–flexible coupling
ISSN:1424-8220, 1424-8220
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Shrnutí:Industrial robotic arms are often subject to significant end-effector pose deviations from the target position due to the combined effects of nonlinear deformations such as link flexibility, joint compliance, and end-effector load. To address this issue, a study was conducted on the analysis and compensation of end-position errors in a six-degree-of-freedom robotic arm. The kinematic model of the robotic arm was established using the Denavit–Hartenberg (DH) parameter method, and a rigid–flexible coupled virtual prototype model was developed using ANSYS and ADAMS. Kinematic simulations were performed on the virtual prototype to analyze the variation in end-effector position errors under rigid–flexible coupling conditions. To achieve error compensation, an approach based on an Enhanced Crayfish Optimization Algorithm (ECOA) optimizing a BP neural network was proposed to compensate for position errors. An experimental platform was constructed for error measurement and validation. The experimental results demonstrated that the positioning accuracy after compensation improves by 75.77%, fully validating the effectiveness and reliability of the proposed method for compensating flexible errors.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s25020378