This paper proposes an adaptive super-twisting global nonsingular terminal sliding mode control (GNTSMC) strategy for robotic manipulators with uncertain perturbations. The strategy aims to achieve finite-time convergence of trajectory errors to the origin, eliminate chattering, and ensure strong robustness throughout the entire response. A novel global nonsingular terminal sliding manifold is designed to steer the system trajectory to the switching surface at the beginning, thereby removing the reaching stage and achieving strong robustness. An adaptive super-twisting algorithm (STA) is then developed to attenuate chattering without degrading tracking precision and to guarantee finite-time stability of the system. The proposed GNTSMC strategy is validated through comparative studies. The dynamic model of a robotic manipulator with uncertain disturbances is described, and the problem formulation is given. The GNTSMC strategy is based on an adaptive STA, which does not require prior information of perturbations and avoids overestimating the adaptive gain. The finite-time stability of the controlled system is proven. Simulation results are provided to demonstrate the effectiveness of the proposed method. The main contributions of this work are: (1) A novel global nonsingular terminal sliding manifold is designed to eliminate the reaching stage, ensuring strong robustness and improved tracking performance. (2) An adaptive STA is developed to suppress chattering without degrading tracking accuracy and to avoid overestimating the adaptive gain. (3) The finite-time stability of the system is analyzed. The proposed GNTSMC strategy is shown to achieve finite-time convergence of the state trajectory to the sliding manifold and drive the trajectory error to the origin within limited time, which differs from previous global SMC methods. The method is validated through simulation results.This paper proposes an adaptive super-twisting global nonsingular terminal sliding mode control (GNTSMC) strategy for robotic manipulators with uncertain perturbations. The strategy aims to achieve finite-time convergence of trajectory errors to the origin, eliminate chattering, and ensure strong robustness throughout the entire response. A novel global nonsingular terminal sliding manifold is designed to steer the system trajectory to the switching surface at the beginning, thereby removing the reaching stage and achieving strong robustness. An adaptive super-twisting algorithm (STA) is then developed to attenuate chattering without degrading tracking precision and to guarantee finite-time stability of the system. The proposed GNTSMC strategy is validated through comparative studies. The dynamic model of a robotic manipulator with uncertain disturbances is described, and the problem formulation is given. The GNTSMC strategy is based on an adaptive STA, which does not require prior information of perturbations and avoids overestimating the adaptive gain. The finite-time stability of the controlled system is proven. Simulation results are provided to demonstrate the effectiveness of the proposed method. The main contributions of this work are: (1) A novel global nonsingular terminal sliding manifold is designed to eliminate the reaching stage, ensuring strong robustness and improved tracking performance. (2) An adaptive STA is developed to suppress chattering without degrading tracking accuracy and to avoid overestimating the adaptive gain. (3) The finite-time stability of the system is analyzed. The proposed GNTSMC strategy is shown to achieve finite-time convergence of the state trajectory to the sliding manifold and drive the trajectory error to the origin within limited time, which differs from previous global SMC methods. The method is validated through simulation results.