Robotic manipulators invariably encounter noise disturbances in practical applications. In the research on motion planning of robotic manipulators, the impact of noise and the optimization of control parameters are often overlooked, which can result in suboptimal noise resistance and prevent robots from successfully completing their tasks. To address this issue, this paper proposes a fuzzy logic-based noise-suppression scheme for motion planning of robotic manipulators. This scheme builds upon the pseudo-inverse method by incorporating error feedback and integral gain to suppress noise. Furthermore, the designed fuzzy rules optimize the control parameters, ensuring effective noise suppression during the robot’s motion planning phase. Finally, through simulations and comparisons, the feasibility and superiority of the proposed fuzzy-rule-based noise-resistant motion planning scheme are validated.