<p>Mobile manipulators hold considerable promise for automating warehouse operations, especially in item picking. However, traditional approaches that alternate between mobile base movement and manipulator operation often suffer from inefficiencies. This inefficiency arises from their discontinuous operational patterns and the resulting suboptimal coordination between locomotion and manipulation. To overcome this limitation and maintain continuous operation, a multimodal hierarchical synergistic strategy is developed. This strategy establishes a dynamic coupling between manipulator gripping actions and mobile base movement, enabling simultaneous operation and improving overall task efficiency. Specifically, the proposed strategy employs the ELD-RRT* algorithm for smooth trajectory planning, guiding the mobile base to both grasping and placement points. To enhance path planning efficiency, the algorithm incorporates ELOA-Sampling, which strategically reduces sampling in unproductive areas. Furthermore, a dynamic expansion step-size strategy is implemented to accommodate specific requirements within the grasping area, ensuring that generated paths meet the manipulator’s grasping stability criteria. To further refine performance, a position-based visual servoing controller is integrated to improve grasping accuracy. Simulation and experimental results demonstrate that, compared to conventional static methods, this mobile grasping strategy enhances task efficiency by 2.5–9.5%.</p>