In this chapter, we present the Multimodal Warehouse Project, which aimed at applying multimodal interaction to a warehouse picking process. We provide an overview of the warehouse picking procedure as well as the overall architecture of the multimodal picking application and technologies applied to design the application. Furthermore, we describe the execution of user tests of the picking appl...

The current study examined the frequency and associated distress of both hairpulling and skin picking behaviors in 1,324 college students using the Massachusetts General Hospital Hairpulling Scale (MGHHS) and Skin Picking Scale (SPS). In this sample, many participants reported significant distress secondary to both hairpulling and skin picking. Participants who endorsed relatively frequent hair...

We present a procedure to perform and interpret pull-off force measurements during the jump-off-contact process between a liquid drop and rough surfaces using a conventional atomic force microscope. In this method, a micrometric liquid mercury drop is attached to an AFM tipless cantilever to measure the force required to pull this drop off a rough surface. We test the method with two surfaces: ...

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...