Modeling and Robust Control for Power Insurance Claim Collaborative Robots Using 3D Gaussian Splash Reconstruction

This paper presents an advanced control algorithm designed to effectively manage trajectory tracking within collaborative robotic systems. The algorithm is based on the assumption of upper bounds for uncertainties inherent in both the dynamic model and external disturbances. The proposed control algorithm integrates traditional proportional-derivative (PD) control with robust control techniques, exhibiting both error-based and model-based characteristics. To establish practical system stability, the Lyapunov minimax method is employed to demonstrate that the system is uniformly bounded and ultimately uniformly bounded. Experimental validation is conducted using a two-degree-of-freedom collaborative robot featuring modular joints, along with the rapid prototype controller system cSPACE. Both numerical simulations and real-time experimental results indicate that the proposed controller substantially enhances the trajectory tracking performance of the robot.