The automation of warehouse operations is crucial for improving productivity and reducing human exposure to hazardous environments. One operation frequently performed in warehouses is bin-packing where items need to be placed into containers, either for delivery to a customer, or for temporary storage in the warehouse. Whilst prior bin-packing works have largely been focused on packing items into empty containers and have adopted collision-free strategies, it is often the case that containers will already be partially filled with items, often in suboptimal arrangements due to transportation about a warehouse. This paper presents a contact-aware packing approach that exploits purposeful interactions with previously placed objects to create free space and enable successful placement of new items. This is achieved by using a contact-based multi-object trajectory optimizer within a model predictive controller, integrated with a physics-aware perception system that estimates object poses even during inevitable occlusions, and a method that suggests physically-feasible locations to place the object inside the container.

翻译：仓库作业的自动化对于提升生产效率和减少人员在危险环境中的暴露至关重要。仓库中频繁执行的一项操作是装箱作业，即需要将物品放入容器中，无论是为了交付给客户，还是为了在仓库中进行临时存储。尽管先前的装箱研究工作主要集中在将物品装入空容器，并采用了无碰撞策略，但实际情况中容器往往已经部分填充了物品，且由于在仓库内的运输过程，这些物品通常处于次优的排列状态。本文提出了一种接触感知的装箱方法，该方法利用与已放置物品的有目的交互来创造可用空间，从而实现新物品的成功放置。这是通过在模型预测控制器中使用基于接触的多物体轨迹优化器来实现的，该控制器集成了一个物理感知的感知系统（即使在不可避免的遮挡情况下也能估计物体姿态），以及一种为容器内物体放置提供物理可行位置建议的方法。