Path planning for mobile manipulator based on energy consumption and grasping accuracy constraints

To increase the efficiency and flexibility of unmanned intelligent warehouses, mobile manipulators can perform tasks such as grasping and handling goods in complex environments and have become a key part of intelligent warehouses. Due to the variety of warehouse tasks and the complex layout of the environment, mobile manipulators often adjust their pose to avoid operational obstacles, which results in wasted resources and additional energy consumption (Ec). In this paper, a path planning method based on iterative optimization for a mobile manipulator is proposed, including path planning for the manipulator and mobile platform separately. First, the workspace of the manipulator and constrained positions of environmental obstacles are analyzed to determine the potential feasible station areas. Then, the feasible trajectory search and optimization of the manipulator in an obstacle environment are achieved based on iterative dynamic programming and a genetic algorithm. Finally, the optimal station is selected by a modified A* algorithm with the minimum total Ec for the mobile platform, robot grasping Ec, and grasping accuracy, and the optimal path for goods grasping and handling is also obtained. A control graphical user interface is developed, and experimental results have shown that the methods proposed in this paper can drastically reduce the total operating Ec of the mobile manipulator under the requirements of robot grasping accuracy, which also ensures that the path planned by the mobile manipulator is practicable and efficient.