This paper considers a problem of in situ estimation of the weight values of individual items that are moving as a bulk on a conveyor in a nonoriented and nonsingulated way. In logistics and material handling processes, it is a challenge to measure the weight of each package moving on a conveyor without halting the conveyor operation. This is not only because measuring weight requires physical contact between the target item and the measuring instrument, but also because each item must be separated (or singulated) from others for it to be weighed. Such a singulation task causes a significant delay in the transport process, especially when the conveyor is heavily loaded with items. Because of this issue, despite the importance of weight information for correct pricing and safe loading (for both air and ground vehicles), the weight has largely been ignored in many logistical sites such as sorting facilities or distribution centers. To address these issues, this paper proposes a new instrumentation device called the in-motion weight sensor (IMWS) array that consists of a grid of mini-checkweighers operating separately from each other as independent weight measurement cells. Each IMWS unit is equipped with a mini-conveyor mounted on a load cell, and provides the composite load data for a group of items being carried within the IMWS system. A depth camera mounted above the IMWS surface identifies both the location and the orientation of each package and provides the real-time measurement of its partial areas that intersect with the surface of load cells in contact with each package. The load cell measurements and the vision data are then fused to construct the measurement equation that is linear in the unknown weight values of all the packages being transported within the IMWS system. To extract individual weight values from these composite load data, we implement the recursive least square (RLS) estimation to the IMWS array. The feasibility of the proposed idea has been verified with experimental tests using the full-scale prototype IMWS array system. The results show that IMWS array is capable of estimating the unknown weight with the mean error around ±3% error and the standard deviation of 9 ~ 13% error for cases where 3 ~ 5 randomly oriented packages are moving in a nonsingulated way.

中文翻译：

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用于动态称重非单一物体的运动中重量传感器阵列

本文考虑了以非定向和非单一化方式在传送带上作为散装移动的单个物品的重量值的原位估计问题。在物流和物料搬运过程中，在不停止输送机运行的情况下测量在输送机上移动的每个包裹的重量是一项挑战。这不仅是因为测量重量需要目标物品和测量仪器之间的物理接触，还因为每个物品必须与其他物品分开（或单独）才能称重。这种分离任务会导致运输过程中的显着延迟，尤其是当输送机装载大量物品时。由于这个问题，尽管重量信息对于正确定价和安全装载（对于空中和地面车辆）很重要，在许多物流场所，例如分拣设施或配送中心，重量在很大程度上被忽略了。为了解决这些问题，本文提出了一种称为动态重量传感器 (IMWS) 阵列的新型仪器设备，该阵列由作为独立重量测量单元相互独立运行的微型检重秤网格组成。每个 IMWS 单元都配备了一个安装在称重传感器上的微型传送带，并为 IMWS 系统内携带的一组物品提供复合载荷数据。安装在 IMWS 表面上方的深度摄像头可识别每个包裹的位置和方向，并实时测量与每个包裹接触的称重传感器表面相交的部分区域。然后将称重传感器测量值和视觉数据融合以构建测量方程，该方程在 IMWS 系统内运输的所有包裹的未知重量值中呈线性。为了从这些复合载荷数据中提取单独的权重值，我们对 IMWS 数组实施了递归最小二乘 (RLS) 估计。已通过使用全尺寸原型 IMWS 阵列系统的实验测试验证了所提出想法的可行性。结果表明，IMWS 阵列能够估计未知重量，平均误差在 ±3% 左右，标准偏差为 9～13%，对于 3~5 个随机定向的包裹以非单一方式移动的情况。为了从这些复合载荷数据中提取单独的权重值，我们对 IMWS 数组实施了递归最小二乘 (RLS) 估计。已通过使用全尺寸原型 IMWS 阵列系统的实验测试验证了所提出想法的可行性。结果表明，对于 3 ~ 5 个随机定向的包裹以非单一方式移动的情况，IMWS 阵列能够估计未知重量，平均误差约为 ±3%，标准偏差为 9 ~ 13%。为了从这些复合载荷数据中提取单独的权重值，我们对 IMWS 数组实施了递归最小二乘 (RLS) 估计。已通过使用全尺寸原型 IMWS 阵列系统的实验测试验证了所提出想法的可行性。结果表明，对于 3 ~ 5 个随机定向的包裹以非单一方式移动的情况，IMWS 阵列能够估计未知重量，平均误差约为 ±3%，标准偏差为 9 ~ 13%。