Dual-arm robots have gained popularity in the field of slabstone handling and installation due to their high efficiency, large load capacity, and strong coordination ability. When these robots use both arms to grab an object, a new type of parallel mechanism is formed. To optimize this mechanism, this paper proposes a robot driving layout optimization method based on motion/force transmission. This method reduces the control difficulty of the robot, improves its kinematics performance, and enhances construction efficiency. The first step in this optimization process involves establishing the forward kinematics model of the robot. Next, the inverse kinematics of the robot is solved using a particle swarm algorithm. This approach streamlines the control process and improves the overall performance of the robot. Then, based on the principle of driving selection, 158 reasonable driving combinations are selected, and 14 combinations are selected as the optimal driving combinations considering the actual engineering situation, and a group of optimal driving combinations is selected with the motion/force transmission performance as the evaluation index. Finally, the impact of various driving combinations on robot accuracy is investigated through experiments. The findings demonstrate that optimizing the driving pair, based on motion/force transmission, enables the robot to execute planned motions effectively and significantly enhances its accuracy. These research outcomes offer theoretical backing for improving the robot’s kinematic performance without altering its topology structure and parameters.