The study of human-human interactions is essential for a better understanding of human behaviour during collaborative tasks. This knowledge is not only interesting in life science but can also be useful in robotic science. Indeed, to efficiently assist a human partner during a human-robot collaboration, the robot needs to be as reactive as a human would be. This can only be achieved by embedding a model of human behaviour into the robot control scheme. In this paper, a human-humanoid robot collaboration to carry a table is tackled. First, the experimental Center of Mass (CoM) trajectories of a table carried by 20 pairs of subjects to various goal positions are studied and modeled using an optimal control problem. Then, based on this model, a prediction process which accurately predicts the table trajectories is designed. Finally, this prediction process is coupled with the robot Walking Pattern Generator (WPG). Using a torque whole-body controller, this framework is tested in simulation on Gazebo on a TALOS humanoid robot model. In this simulation, the robot actively assists a simulated human partner in lifting and carrying a table to an unknown goal position.