Abstract—This paper presents a method for identifying the hazardous configuration of a KUKA KR3 R540 Six-Degree-of-Freedom (6-DOF) industrial robot. A kinematic model is first established using the standard Denavit-Hartenberg (D-H) method, and a multi-body dynamic model is subsequently constructed by incorporating the Newton-Euler formulation. To identify the pose that induces the maximum joint torque, a search strategy based on the Particle Swarm Optimization (PSO) algorithm is proposed, implemented through co-simulation between Adams and MATLAB. The optimization objective is defined as maximizing the sum of the absolute driving torques of joints J2 to J6, with the corresponding joint angles serving as decision variables. The PSO algorithm, driven by MATLAB, generates candidate poses, while Adams performs high-precision dynamic computations. This framework enables an automated search across the high-dimensional joint space to iteratively locate the global optimum. Simulation results demonstrate that the proposed method effectively identifies the global most hazardous configuration, corresponding to a fully extended manipulator pose with J2 ≈ −90.81° and J3 ≈ 82.57°. The maximum total joint torque in this configuration is approximately 182.47 Nꞏm. These results provide crucial load boundary conditions for structural strength verification and lightweight design, while also offering valuable insights for the selection of key components in structural optimization.

Keywords—KUKA robot, dynamic analysis, hazardous configuration, Particle Swarm Optimization (PSO), Adams-MATLAB co-simulation

Cite: Lina Zhang and Aldrin D. Calderon, "Particle Swarm Optimization-Based Hazardous Configuration Identification and Dynamic Analysis for Industrial Robots," International Journal of Mechanical Engineering and Robotics Research, Vol. 15, No. 1, pp. 38-49, 2026. doi: 10.18178/ijmerr.15.1.38-49

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).