With the rapid development of the industrial robotics industry, mobile robots are increasingly deployed in indoor environments for tasks such as grasping, transporting, and placing objects. While existing servo control methods can handle basic manipulation tasks, they often treat the mobile base and the manipulator as decoupled subsystems, leading to inefficient planning and prolonged execution times. To address these limitations, this paper proposes a visual servoing approach for collaborative placement based on the fusion of heterogeneous degrees of freedom. This method enables coordinated control between the mobile base and the manipulator, significantly enhancing task efficiency. A hardware platform comprising a mobile base, robotic arm, depth camera, and industrial computer is constructed through comparative component selection. On this platform, a complete software system based on the Robot Operating System (ROS) is developed, including perception, planning, and execution modules. Real-world experiments in indoor environments are conducted for grasping and placement tasks, achieving an overall execution time of 45 s. Compared to conventional mobile robot servo control methods, the proposed system demonstrates a 90% success rate and notable improvements in responsiveness and task performance, validating its effectiveness and practicality.