Analysis of Manipulator Motion Performance Based on Numerical Simulation and Intelligent Path Planning Algorithm
DOI: 10.23977/jemm.2026.110206 | Downloads: 0 | Views: 35
Author(s)
Yuxuan Wang 1
Affiliation(s)
1 Brunel London School, North China University of Technology, Shijingshan District, Beijing, 100144, China
Corresponding Author
Yuxuan WangABSTRACT
To address issues such as vibration, trajectory irregularity, and insufficient motion stability in four-degree-of-freedom SCARA manipulators under high-speed operation, this paper proposes a comprehensive motion performance analysis method combining finite element numerical simulation with path planning algorithms. Using a four-degree-of-freedom SCARA manipulator as the research object, an ANSYS Workbench-based finite element model was established to conduct static, modal, and harmonic response analyses, evaluating structural strength, stiffness, and dynamic stability. A MATLAB-based kinematic model of the manipulator was developed, employing the PCHIP piecewise cubic interpolation method to design smooth obstacle-avoidance paths in static obstacle environments, followed by motion simulation validation. Results indicate: the manipulator exhibits a maximum equivalent stress of 216 MPa, maximum end deformation of 0.13 mm, and a first-order natural frequency of 54.04 Hz, showing no significant resonance response under periodic excitation, meeting strength and dynamic stability requirements. The proposed path planning method generates continuous smooth trajectories, achieving safe obstacle avoidance and stable tracking. The study achieves coordinated evaluation of path planning and structural performance, providing theoretical foundations and technical references for the engineering application and optimal design of SCARA manipulators.
KEYWORDS
SCARA robotic arm; Finite element analysis; Path planning; Motion performance; Obstacle avoidance controlCITE THIS PAPER
Yuxuan Wang. Analysis of Manipulator Motion Performance Based on Numerical Simulation and Intelligent Path Planning Algorithm. Journal of Engineering Mechanics and Machinery (2026). Vol. 11, No. 2, 54-63. DOI: http://dx.doi.org/10.23977/jemm.2026.110206.
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