Base position optimization of mobile manipulators for machining large complex components

With good mobility and high flexibility, the mobile manipulator shows a broad application prospect in the machining of large complex components. In these applications, in order to fully utilize the capabilities of the robot, it is usually necessary to design a series of suitable working positions (i.e. robot's base position) for the mobile manipulator. However, the performance distribution of the robot in the task space is highly nonlinear, which makes it difficult to determine the optimal base positions. Therefore, this paper proposes a new base position optimization method, which can accurately find the optimal base position that takes into account both kinematics and stiffness performance. First, a task-oriented performance index MSPI (mean stiffness performance index) is proposed to evaluate the global stiffness performance of the robot. Based on MSPI, an optimization model considering multiple constraints such as joint range, joint speed, singular avoidance and collision avoidance is established. The optimization model is solved by sparse uniform grid decomposition and Sequential Quadratic Programming (SQP) method, the former is used to find a suitable initial value, the latter is used to determine the optimal base position. Finally, simulation analysis and experiments confirmed the effectiveness of the optimization method and the correctness of the performance index MSPI.