Accurate rigid-body dynamics is crucial for serial industrial robot applications such as force control and physical human-robot interaction. Despite decades of research, the precise identification of dynamic parameters—particularly low-magnitude inertia parameters—remains a challenge for serial industrial robots. Researchers usually focus on developing various parameter estimation methods, while optimizing exciting trajectories in similar ways, typically minimizing the condition number of the information matrix. However, such optimization usually fails to ensure sufficient excitation for each parameter, due to non-convex coupling effects. To address this limitation, we propose a fully decoupled rigid-body dynamics identification (FDRDI) method in this article. This approach innovatively eliminates coupling effects by using novel symmetrical exciting trajectories based on reciprocating S-curve (RSC). This innovation enables the independent identification of dynamic parameters associated with joint friction, as well as the gravity and inertia of links and payloads. Comparative experiments show that FDRDI achieves superior identification accuracy, evidenced by reduced joint torque prediction errors and payload parameter estimation errors.