Surrogate modeling for time-dependent reliability analysis of robotic manipulator trajectories.

ABSTRACT: The kinematic reliability analysis of robotic manipulators is crucial due to uncertainties such as joint variations, manufacturing tolerances, and external disturbances. Traditional methods often rely on analytical techniques that struggle with nonlinear performance functions and fail to account for trajectory-based reliability. To overcome these limitations, this paper proposes a novel surrogate model-based approach using Kriging to estimate the reliability of robotic manipulator kinematics while considering end-effector trajectories. The methodology begins with building an initial Kriging surrogate model to analyze reliability, effectively capturing how input uncertainties influence trajectory accuracy. This model is then refined through statistical sampling techniques, ensuring an effic

SUBMITTER: Ayoob K 

PROVIDER: S-EPMC12483274 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature