Human supported picking stations are commonly used in warehouses across various business sectors. So called goods-to-man picking processes are usually guided by simple cross-checks to minimize picking errors. These cross-checks typically utilize binary light-barriers and are hence not able to accurately identify wrong picks or even provide early warnings to operators. In this work, we present a...

Picking machines, also known as remote-order-picking systems, are an example of a stock-to-picker piece-level order-fulfillment technology that consists of two or more pick stations and a common storage area. An integrated closed-loop conveyor decouples the pick stations from the storage area by transporting the needed totes to and from the storage area and the pick stations. We develop a proba...

The performance of a distribution center is typically judged on throughput-based criteria. Order picking consumes 30% to 40% of operation time in a typical distribution center. To effectively execute an order picking operation in a distribution center depends upon coordinating the formulation of the storage strategy, order processing, and planning the order picking route. However, it is usually...

OBJECTIVE This article proposes a method to automatically identify and label event-related potential (ERP) components with high accuracy and precision. METHODS We present a framework, referred to as peak-picking Dynamic Time Warping (ppDTW), where a priori knowledge about the ERPs under investigation is used to define a reference signal. We developed a combination of peak-picking and Dynamic ...

To solve the problem that robot often collides with obstacles such as branches around fruit during picking due to its inability adapt growing environment, this paper proposes an apple-picking path planning algorithm based on improved PSO. The main contents of are: firstly, and surrounding are extracted from 3D point cloud data, direction is calculated; then surface used establish spatial model ...

For the peak picking of tempo candidates, applying kmeans clustering on tempo curve is straightforward and leading to good result. But the tempo candidates obtained from tempo curve are limited and lose a lot of information for possible tempi. The study proposes the local maximum peak picking method to increase the number and information of possible tempo candidates. Therefore, the accuracy of ...