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Planning a Sequence of Base Positions for a Mobile Manipulator IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. SUBMISSION FOR REVIEW, 2020 1 Planning a Sequence of Base Positions for a Mobile Manipulator to Perform Multiple Pick-and-Place Tasks Jingren Xu, Student Member, IEEE, Yukiyasu Domae, Member, IEEE, Toshio Ueshiba, Member, IEEE, Weiwei Wan, Member, IEEE, and Kensuke Harada, Senior Member, IEEE Abstract—In this paper, we present a planner that plans a sequence of base positions for a mobile manipulator to effi- ciently 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 Fig. 1: A schematic diagram of the storage area in an assembly of the tasks. In the experiment part, we examine our planner factory, a mobile manipulator is used to replace human workers on various scenarios, including different object placement: (1) to pick up objects from multiple places and then transport to the Regularly placed toy objects; (2) Randomly placed industrial assembly line for further assembly. 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, base and a manipulator, is able to navigate and manipulate robustness and feasibility of the proposed method. in human environment. Therefore, mobile manipulators are Note to Practitioners—The presented project uses mobile ma- promising for serving human environment and performing a nipulators to fetch and supply parts in an automotive assembly variety of tasks in a large work space. Especially, the mobile factory. Mechanical parts at these sites are usually regularly or manipulator is suitable for picking up objects and transporting randomly placed in supply trays. The project develops methods to explore robust mobile base positions where the objects with them to the desired position. One example of such multiple different placement styles and from different trays can be reached pick-and-place tasks is the part-supply task in manufacturing by a mobile manipulator. The mobile manipulators could perform environment, such as in an automotive assembly factory, where efficient and high-quality pick-and-place operations by navigating a huge amount of assembly components of an automobile are to the explored positions. The developed methods also discuss scattered in a large storage area (Fig. 1). Currently human the dynamic updates the base positions following picking process to further increase system robustness. The presented project is workers are still highly engaged in the part-supply task and expected to shed light on the deployment of mobile manipulators they have to go back and forth to fetch required assembly arXiv:2010.00779v1 [cs.RO] 1 Oct 2020 to collect parts at large manufacturing factories. components from trays in different locations, and then carry Index Terms—Mobile manipulation; Multiple pick-and-place the collected components to the assembly area. It is promising tasks; Manufacturing automation. to apply mobile manipulators to replace human workers and automate this part-supply process, owning to their ability of moving and picking. I. INTRODUCTION In order to assemble a product P, which is comprised of HERE is an increasing demand on robots which are several types of parts Pa, Pb and Pc, stored in different trays able to flexibly assist human in daily work and indus- T tray1, tray2 and tray4, respectively, the mobile manipulator trial production. A mobile manipulator, combining a mobile may have to move to a sequence of positions to gradually pick J. Xu, W. Wan and K. Harada are with Graduate School of En- up the required assembly parts from different trays. The base gineering Science, Osaka University, Osaka 560-8531, Japan. J. Xu sequence are comprised of a series of base positions, in which and K. Harada are also with Artificial Intelligence Research Cen- the mobile manipulator is able to grasp the required assembly ter, National Institute of Advanced Industrial Science and Technology (AIST), Japan (e-mail: [email protected]; [email protected] parts from the trays without self-collision and the collision u.ac.jp; [email protected]). with the environment. To collect the required parts from the Y. Domae and T. Ueshiba are with Artificial Intelligence Research Center, target trays, we can simply move the mobile manipulator to National Institute of Advanced Industrial Science and Technology (AIST), Japan (e-mail: [email protected]). the position in front of every target tray, alternatively, we can Manuscript received Month 00, 0000. move the mobile manipulator to the position where the mobile IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. SUBMISSION FOR REVIEW, 2020 2 manipulator can reach the parts stored in multiple trays, and II. RELATED WORK then the mobile manipulator carries the collected assembly parts to the designated area for further assembly. Early work in mobile manipulation proposed rich theoretical analysis and concepts, which are extensively used as the evalu- However, with increased base sequence size, the overall op- ation metrics in later work. They were mainly concerned with eration time increases significantly for the following reasons: the kinematics and dynamics modeling of mobile manipulator (1) The mobile manipulator decelerates and then accelerates [1], [2], resolution of the kinematic redundancy caused by the at every base position of the base sequence, which lowers mobile base [3], [4], coordinated control of mobile base and the overall base velocity and increases the total operation manipulator arm [5], and the manipulability analysis of the time. (2) Every time the mobile manipulator experiences a mobile manipulator [6], [7]. ”stop and manipulation”, there is risk that the arrived position More recently, there have been numerous work on motion significantly deviates from the desired position, then the mo- planning of mobile manipulator [8], [9], [10] and optimal base bile manipulator has to perform time-consuming repositioning position planning for achieving certain design criteria, such process, and the risk accumulates with expanding base se- as manipulability, end effector poses and velocity [11], and quence. Therefore, it is crucial to prune out unnecessary base reaching/grasping a set of targets [12], [13]. Du et al. [14] movements to improve the overall efficiency. used the manipulability index to determine a suitable base To simplify the base sequence for the general multiple placement. Ren et al. [11] optimized the base positions for a pick-and-place tasks, it is preferable to move the mobile mobile manipulator to reach a set of positions with required manipulator to the position, in which the mobile manipulator orientations and keep a stable velocity in local painting tasks. is able to pick up the assembly parts from multiple trays. As Berenson et al. [8] obtained the base placement and grasp for a shown in Fig. 1, the mobile manipulator moves to the first mobile manipulator to move an object from one configuration base position and is able to grasp the assembly parts in both to another, by optimizing a scoring function which combines tray1 and tray2, thus reduces the base sequence size by one. the grasp quality, manipulability and distance to obstacle. To obtain such positions, we first calculate the base region for OpenRAVE [15] provides an inverse reachability module, every target tray in the given assembly task, the base region is which clusters the reachability space for a base-placement a set of base positions where the mobile manipulator can grasp sampling distribution that can be used to find out where the the target assembly parts from that tray without collision. robot should stand in order to perform a manipulation task. Then the intersections of these base regions are given high Stulp et al. [16] proposed Action-Related Place to associate priority in the base sequence planning. Moreover, the base a base location with a probability of successfully performing positioning uncertainty is considered in the base sequence a manipulation task, capability map was used to determine planning by restricting the size of the applicable intersections, if an object was theoretically reachable. Burget et al. [12] the intersections smaller than the base positioning uncertainty employed the inverse reachability map to select statically are discarded, otherwise the mobile manipulator is likely to stable, collision-free stance configurations for a humanoid move out the intersection due to the unavoidable positioning robot to reach a given grasping target. Zacharias et al. [17] error. With the calculated base regions and robust intersections, took advantage of the reachability map to position a mobile we plan the shortest path that visit all the target trays with manipulator to perform a linear trajectory in the workspace. minimal number of base movements. Following the planned Vahrenkamp [18] conducted a series of research on reachabil- base sequence, the mobile manipulator can perform efficient ity analysis and its application, the base positions with high and robust part-supply tasks in real world applications. probability of reaching a target pose can be efficiently found The base sequence planning can be implemented in multiple from the inverse reachability distribution. The reachability forms, depending on the definition of the ”target” objects. indicates the probability of finding an IK solution, while there Firstly, if the target objects are all the objects which fill up is no guarantee on the completeness of obtained base positions.
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