Structural Parameter Optimization of Robotic Arm Based on ABAQUS

Abstract

The structural parameters of robotic arms are crucial for industrial production safety and cost efficiency. However, the complex relationships between structural parameters (e.g., cross-sectional shape, area ratio, and rear-end area) and mechanical performance are challenging to express using simple mathematical formulas. To scientifically predict the load-bearing capacity of robotic arms with specific structural parameters, this study employs ABAQUS software to conduct static load simulations on robotic arms with varying parameters. The simulation data are optimized using the NSGA-2 algorithm to generate a Pareto solution set for maximum stress and displacement. Subsequently, the entropy weight method is applied to calculate the weights of these two indicators, and the TOPSIS algorithm is utilized to screen the optimal solution. The results demonstrate that under a given load, the robotic arm with a circular cross-section, an area ratio of 0.96, and a rear-end area of 39.80 mm² exhibits the highest load-bearing capacity. Compared with traditional robotic arm optimization methods, this paper combines the comprehensive evaluation method with the multi-objective optimization method to achieve the goal of selecting the best among the best data of the robot arm in the optimization solution set. This method can not only meet the requirements of the robot arm for the structure and mechanical properties, but also make the optimization results more excellent, which has important guiding significance for improving the manufacturing process design of the robot arm.