Research on Task Allocation Method for Dual-Robot Stereoscopic Stone Carving Under Stiffness Constraints

Multi-robot systems, owing to their parallel operation and cooperative capabilities, have become an important means of improving the efficiency of complex workpiece machining. However, task allocation methods directly determine the overall system performance, which is particularly critical in scenarios with high curvature and stringent stiffness requirements. This study focuses on a Dual-Robot Carving System (DRCS) and proposes a task allocation method that incorporates stiffness performance constraints, using stereoscopic stone carving as a representative application. First, a workstation optimization model is developed based on the average normal stiffness as the evaluation metric, enabling the selection and allocation of high-complexity tasks. This approach not only ensures machining stiffness but also effectively decouples the task allocation problem. Subsequently, two allocation strategies are designed for low-complexity tasks: one based on machinability and the other on machining time balancing. Comparative simulations and physical experiments are conducted to evaluate the efficiency differences between the proposed methods and the single-robot machining mode. The results show that the machining time balancing strategy improves efficiency by 14.33% compared with the machinability-based strategy, and by 84.78% compared with the single-robot mode. These findings demonstrate the effectiveness of the proposed method in enhancing dual-robot collaborative efficiency and provide a novel modeling perspective and technical support for multi-robot task allocation under stiffness constraints in complex workpiece machining.