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In this paper, we address efficiently and robustly collecting objects stored in different trays using a mobile manipulator. A resolution complete method, based on precomputed reachability database, is proposed to explore collisionfree inverse kinematics (IK) solutions and then a resolution complete set of feasible base positions can be determined. This method approximates a set of representative IK solutions that are especially helpful when solving IK and checking collision are treated separately. For real world applications, we take into account the base positioning uncertainty and plan a sequence of base positions that reduce the number of necessary base movements for collecting the target objects, the base sequence is robust in that the mobile manipulator is able to complete the part-supply task even there is certain deviation from the planned base positions. Our experiments demonstrate both the efficiency compared to regular base sequence and the feasibility in real world applications.

In this paper, we present a structured approach of selecting and designing a set of grippers for an assembly task. Compared to current experience-based gripper design method, our approach accelerates the design process by automatically generating a set of initial design options on gripper type and parameters according to the CAD models of assembly components. We use mesh segmentation techniques to segment the assembly components and fit the segmented parts with shape primitives, according to the predefined correspondence between primitive shape and gripper type, suitable gripper types and parameters can be selected and extracted from the fitted shape primitives. Then considering the assembly constraints, applicable gripper types and parameters can be filtered from the initial options. Among the applicable gripper configurations, we further minimize the required number of grippers for performing the assembly task, by exploring the gripper that is able to handle multiple assembly components during the assembly. Finally, the feasibility of the designed grippers are experimentally verified by assembling a part of an industrial product.

In this paper, we present a planner that plans a sequence of base positions for a mobile manipulator to efficiently and robustly collect objects stored in distinct trays. We achieve high efficiency by exploring the common areas where a mobile manipulator can grasp objects stored in multiple trays simultaneously and move the mobile manipulator to the common areas to reduce the time needed for moving the mobile base. We ensure robustness by optimizing the base position with the best clearance to positioning uncertainty so that a mobile manipulator can complete the task even if there is a certain deviation from the planned base positions. Besides, considering different styles of object placement in the tray, we analyze feasible schemes for dynamically updating the base positions based on either the remaining objects or the target objects to be picked in one round of the tasks. In the experiment part, we examine our planner on various scenarios, including different object placement: (1) Regularly placed toy objects; (2) Randomly placed industrial parts; and different schemes for online execution: (1) Apply globally static base positions; (2) Dynamically update the base positions. The experiment results demonstrate the efficiency, robustness and feasibility of the proposed method.Note to Practitioners-The presented project uses mobile manipulators to fetch and supply parts in an automotive assembly factory. Mechanical parts at these sites are usually regularly or randomly placed in supply trays. The project develops methods to explore robust mobile base positions where the objects with different placement styles and from different trays can be reached by a mobile manipulator. The mobile manipulators could perform efficient and high-quality pick-and-place operations by navigating to the explored positions. The developed methods also discuss the dynamic updates the base positions following picking process to further increase system robustness. The presented project is expected to shed light on the deployment of mobile manipulators to collect parts at large manufacturing factories.

Mobile manipulators are able to operate in a large workspace, and have the potential to replace human workers to perform a sequence of pick-and-place tasks at separate locations. Many existing works optimize the base position or manipulator configuration for a single manipulation task, however, very few of them consider a sequence of tasks. In this paper, we present a planner that plans a minimum sequence of base positions for a mobile manipulator to robustly collect objects stored in multiple trays. We use inverse kinematics to determine the base region where a mobile manipulator can grasp the target objects stored in a tray, and move the mobile manipulator to the intersections of base regions to reduce the operation time for moving the base. We ensure robustness by only considering the intersection whose radius of the inscribed circle is larger than the base positioning error. Then the minimization of the number of base positions is formulated as a 0-1 knapsack problem. Besides, considering different object placements in the tray, we analyze feasible policies for dynamically updating the base sequence based on either the remaining objects or the target objects to be picked. In the experiment, we examine our planner on various scenarios, including different object placements: (1) Regularly placed toy objects; (2) Randomly placed industrial parts; and different implementation policies: (1) Apply globally static base positions; (2) Dynamically update the base positions. The experiment results show that the time for moving the base decreases by 11.22 seconds (29.37%) to 17.26 seconds (36.77%) by reducing one base movement, and demonstrate the feasibility and potential of the proposed method.INDEX TERMS Mobile manipulation, manufacturing automation, part-supply tasks, pick-and-place, tasklevel planning.

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