Bi-Objective Station Planning of a Mobile Manipulator Considering Dexterity and Stiffness for Robotic 3D Concrete Printing

This study investigates the station planning problem of a mobile manipulator for robotic 3D concrete printing. The problem is formulated as a station planning problem considering two trajectory-level performance objectives: kinematic dexterity and structural stiffness. A directional dexterity metric based on the minimum normalized velocity directional manipulability along the task path is used to evaluate the worst-case motion capability of the manipulator during trajectory execution. A stiffness-related metric based on the maximum absolute Z-axis deformation of the end-effector is used to evaluate the worst-case deformation under operational loads. These two trajectory-level criteria are normalized and integrated through a weighted scalarization strategy, and a genetic algorithm is employed to search for station configurations under reachability constraints. Case studies on representative wall geometries show that the proposed method improves motion performance and reduces deformation compared with non-optimized station placements. The results indicate that the proposed framework provides an effective station planning strategy for mobile manipulators in trajectory-following robotic tasks.