Planning a Sequence of Base Positions for a Mobile Manipulator to Perform Multiple Pick-and-Place Tasks

Abstract

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.

HCDR-based motion planning for mobile manipulators with the continuous trajectory task

“…Gonc xalves et al 9 compared the efficiency and effectiveness of four state-of-the-art evolutionary algorithms considering the collision avoidance for the mobile manipulator, and found that Parato-based algorithms are suitable for off-line trajectory planning. Xu et al 10 presented a base positions planning method to search for the shortest path for a mobile manipulator, including steps of IK solutions, reachability database construction, base positioning uncertainty analysis and path planning. Pajak and Pajak 11 described a holonomic mobile humanoid manipulator and proposed its motion planning under an industrial environment, which considers mechanical limitations, collisions avoidance and manipulation dexterity.…”