Optimal joint space control of palletizing robot applied to tea caddy sorting

To simulate the palletizing robot product line for tea caddy sorting, an optimal controller with a fast-continuous nonsingular terminal sliding mode control strategy was proposed. After designing a three-dimensional model of the product line, the dynamical model of the palletizing robot was deduced through the Lagrangian equation, which was clarified the inputs and outputs of the system. Then, an artificial intelligence algorithm called glowworm swarm optimization algorithm was used for trajectory planning. The fifth-order polynomial interpolation method and NUBRS curve were introduced to smooth the trajectories（i.e., referenced trajectories）. Furthermore, a fast-continuous nonsingular terminal sliding mode control strategy was designed to accelerate the convergence of the state variables in the system, which can improve the trajectory tracking precision in joint space. Lastly, series of simulation cases were conducted to test the proposed method. The results show that the proposed controller had a higher control performance than the sliding mode and backstepping controllers. The glowworm swarm optimization algorithm could help the robot obtain optimal joint trajectories of 0.37 s. The proposed controller could retrain the lumped torques and ensure the trajectory tracking precision in joint space.