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Control of the humanoid robots requires appropriate gait planning that satisfies stable walking. In this study, a Modified Transpose Jacobian (MTJ) control algorithm for object manipulation by two humanoid robots is developed. Such cooperative humanoid robots may typically get employed in hazardous situation and industrial applications. In the present paper, a high performance and robust controller was developed for the safe load handling, transportation and trajectory tracking. The MTJ algorithm, based on an approximated feedback linearization approach, employs stored data of the control command in the previous time step, to yield an improved performance. First, dynamic equations of the robot were derived. In order to verify the obtained dynamics equations, another model for the considered system has been developed using Matlab/SimMechanics simulation software. Comparison between the results obtained from these two dynamics models confirms the validity of the proposed analytical approach. Then, the stable walking gait based on ZMP approach was planned. Furthermore, the MTJ controller was applied to the robots and for comparison, the Transpose Jacobian (TJ) was also utilized. Significantly, it is shown that the MTJ yields smaller trajectory tracking errors than the TJ controller, without requiring high gains as TJ or extra computations as model-based algorithms which may not be feasible for on-line implementations.