Dynamic balance control for humanoid robots encounters difficulties such as stability, speed, and smoothness. In most of the previous studies, joints act as controller of the Center of Mass (CoM)supported using a simplified mathematical model. Then, the stability of the motion is guaranteed using the Zero Moment Point (ZMP)stability criterion. In this video, a humanoid robot  will carry a tray secured to the wrist and the objects to be transported will be placed on the tray. This condition implies that the object is not grasped and therefore, the robot arm will be the only point of support of the object through the tray. Thus, the manipulation control system must be able to detect the stability of the object and act according to the different perturbations applied to it. A 3D balance control system for non-grasping tasks is presented and it is based on the ZMP criterion and 3D inverted pendulum equations. The perception system required is based on the use of Force-Torque sensors , computer vision , and their integration. The effectiveness of the proposed approach is being investigated with the humanoid robot TEO.