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    Enhancing depth cues with AR visualization for forklift operation assistance in warehouse. (2016)

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    Sarupuri, Bhuvan_Final Masters Thesis.pdf (3.464Mb)
    Type of Content
    Theses / Dissertations
    UC Permalink
    http://hdl.handle.net/10092/12038
    http://dx.doi.org/10.26021/2612
    
    Thesis Discipline
    Human Interface Technology
    Degree Name
    Master of Human Interface Technology
    Publisher
    University of Canterbury
    Language
    English
    Collections
    • Engineering: Theses and Dissertations [2759]
    Authors
    Sarupuri, Bhuvaneswari
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    Abstract

    With warehouse operations contributing to the major part of logistics, architects tend to utilize every inch of the space allocated to maximize the stacking space. Increasing the height of the aisles and narrowing down the aisle-aisle space are major design issues in doing so. Even though forklift manufacturing companies introduced high reach trucks and forklifts for narrow aisles, forklift operators face many issues while working with heavy pallets. This thesis focused on developing a systemthat uses Augmented Reality(AR) to aid forklift operators in performing their pallet racking and pick up tasks. It used AR technology to superimpose virtual cues over the real world specifying the pallets to be picked up and moved and also assist in operating the forklift using depth cues. This aims to increase the productivity of the forklift operators in the warehouse. Depth cues are overlaid on a live video feed from a camera attached to the front of the forklift which was displayed using a laptop to the participants. To evaluate the usability of the system designed, an experiment was conducted and the performance results and the feedback from the participants was evaluated. A remote controlled toy forklift was used to conduct the experiment and a motion tracking system was set-up to track the cab and pallet. Simple pallet handling tasks were designed for the participants and their performance and feedback was collected and analysed. This thesis shows how AR offers a simple and effecient solution for the problems faced by forklift operators while performing pallet handling tasks in warehouse.

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