Multi-Step Object Extraction Planning From Clutter Based on Support Relations
Multi-Step Object Extraction Planning From Clutter Based on Support Relations
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DOI：
10.1109/access.2023.3273289
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发表时间：
2023
期刊：
影响因子：
3.9
通讯作者：
Tomohiro Motoda;Damien Petit;Takao Nishi;K. Nagata;Weiwei Wan;K. Harada
中科院分区：
文献类型：
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作者：
Tomohiro Motoda;Damien Petit;Takao Nishi;K. Nagata;Weiwei Wan;K. Harada
为了实现物流仓库的自动化操作，机器人需要从货架上的杂乱物品中提取物品，而不会将杂乱物品折叠。为了解决这一问题，本研究提出了一种多步运动规划器，利用杂波中包含的每个目标的支持关系来稳定地提取项目。本研究主要关注安全提取，这使得机器人能够在有限的观察基础上选择最佳的下一步行动。通过对支撑关系的估计，构造一个塌陷预测图，得到合适的目标提取顺序。因此，可以在不破坏桩的情况下提取目标物体。此外，我们还表明，如果机器人使用一只手臂提取目标物体，而另一只手臂支撑邻近物体，则可以提高机器人的效率。在支持关系检测和目标提取任务的实际实验中对该方法进行了评估。实验结果表明，该机器人可以基于塌陷预测估计支撑关系，并在真实环境中进行安全提取。我们的多步提取方案确保了更好的性能和鲁棒性，以实现从杂乱中安全的目标提取任务。
To automate operations in a logistic warehouse, a robot needs to extract items from the clutter on a shelf without collapsing the clutter. To address this problem, this study proposes a multi-step motion planner to stably extract an item by using the support relations of each object included in the clutter. This study primarily focuses on safe extraction, which allows the robot to choose the best next action based on limited observations. By estimating the support relations, we construct a collapse prediction graph to obtain the appropriate order of object extraction. Thus, the target object can be extracted without collapsing the pile. Furthermore, we show that the efficiency of the robot is improved if it uses one of its arms to extract the target object while the other supports a neighboring object. The proposed method is evaluated in real-world experiments on detecting support relations and object extraction tasks. This study makes a significant contribution because the experimental results indicate that the robot can estimate support relations based on collapse predictions and perform safe extraction in real environments. Our multi-step extraction plan ensures both better performance and robustness to achieve safe object extraction tasks from the clutter.