Where to relocate?: Object rearrangement inside cluttered and confined environments for robotic manipulation

Where to relocate?: Object rearrangement inside cluttered and confined environments for robotic manipulation
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搬迁到哪里?:在杂乱且受限的环境中重新排列对象以进行机器人操作

DOI:
10.1109/icra40945.2020.9197485
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发表时间:
2020
期刊:
2020 IEEE International Conference on Robotics and Automation (ICRA)
影响因子:
--
通讯作者:
Changjoo Nam
Changjoo Nam
中科院分区:
--
文献类型:
--
作者:
S. Cheong;Brian Y. Cho;Jinhwi Lee;Changhwan Kim;Changjoo Nam

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我们提出了一种算法,确定在哪里重新定位对象内的一个混乱和有限的空间,同时重新安排对象检索目标对象。虽然已经提出了决定要删除什么的方法,但在工作空间内放置删除对象的规划并没有得到太多的关注。相反,被移除的对象通常被放置在工作空间之外,这导致额外的费力工作(例如,操纵器和移动的基座的运动规划和执行、其它区域的感知)。在这项工作中,我们考虑了单调(每个对象只移动一次)和非单调排列问题,这些问题已经被证明是$\mathcal{N}\mathcal{P}$-hard的。一旦要重新定位的对象的序列是由任何现有的算法,我们的方法的目的是最大限度地减少拾取和放置动作的数量,放置对象,直到目标变得可访问。从大量的实验中,我们表明,我们的方法减少了取放动作的数量和总执行时间(减少分别高达23.1%和28.1%)相比,基线方法,同时实现更高的成功率。
We present an algorithm determining where to relocate objects inside a cluttered and confined space while rearranging objects to retrieve a target object. Although methods that decide what to remove have been proposed, planning for the placement of removed objects inside a workspace has not received much attention. Rather, removed objects are often placed outside the workspace, which incurs additional laborious work (e.g., motion planning and execution of the manipulator and the mobile base, perception of other areas). Some other methods manipulate objects only inside the workspace but without a principle so the rearrangement becomes inefficient.In this work, we consider both monotone (each object is moved only once) and non-monotone arrangement problems which have shown to be $\mathcal{N}\mathcal{P}$-hard. Once the sequence of objects to be relocated is given by any existing algorithm, our method aims to minimize the number of pick-and-place actions to place the objects until the target becomes accessible. From extensive experiments, we show that our method reduces the number of pick-and-place actions and the total execution time (the reduction is up to 23.1% and 28.1% respectively) compared to baseline methods while achieving higher success rates.
DOI: 10.1177/0278364918780999
发表时间: 2017-11
期刊: The International Journal of Robotics Research
影响因子: --
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影响因子: 5.2
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发表时间: 2018
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