A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones
In this paper, a mathematical model and solution for performing the inventory tasks of a multi-user, mixed warehouse in which neither satellite positioning nor other IT solutions can be used was presented. After reviewing the literature on road planning and the use of drones in warehouses, a method...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/6/11/364 |
| _version_ | 1797465539418783744 |
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| author | Miklós Gubán József Udvaros |
| author_facet | Miklós Gubán József Udvaros |
| author_sort | Miklós Gubán |
| collection | DOAJ |
| description | In this paper, a mathematical model and solution for performing the inventory tasks of a multi-user, mixed warehouse in which neither satellite positioning nor other IT solutions can be used was presented. After reviewing the literature on road planning and the use of drones in warehouses, a method is presented that can be used to control drones that can be moved in all directions for imaging and transmission. The proposed method consists of three main steps. As a first step, we provide the mathematical model and solution method needed to determine the (optimal execution time) access routes required for processing the compartments of the warehouses. This is an initial step before starting the inventory. This considers the structure of the warehouse, its features, the number of drones, and the parameters of the drones. In the second step, based on the routes obtained in the first step, the real-time movement of the drones was controlled during processing, including camera movement and image recording. The third step is post-processing, i.e., processing the images for QR code identification, interpreting the QR code, and recognizing empty compartments for inventory control. A major advantage for users of the solution method is that the result can be achieved automatically without an external orientation device, relying solely on its own movement and the organization of a pre-planned route. The proposed model and solution method are suitable not only for inventory control, but also for solving other problems matching the model. |
| first_indexed | 2024-03-09T18:23:54Z |
| format | Article |
| id | doaj.art-ddea9a63ca504866a6d85ac7a4fb50ce |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-09T18:23:54Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-ddea9a63ca504866a6d85ac7a4fb50ce2023-11-24T08:06:58ZengMDPI AGDrones2504-446X2022-11-0161136410.3390/drones6110364A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of DronesMiklós Gubán0József Udvaros1Faculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, HungaryFaculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, HungaryIn this paper, a mathematical model and solution for performing the inventory tasks of a multi-user, mixed warehouse in which neither satellite positioning nor other IT solutions can be used was presented. After reviewing the literature on road planning and the use of drones in warehouses, a method is presented that can be used to control drones that can be moved in all directions for imaging and transmission. The proposed method consists of three main steps. As a first step, we provide the mathematical model and solution method needed to determine the (optimal execution time) access routes required for processing the compartments of the warehouses. This is an initial step before starting the inventory. This considers the structure of the warehouse, its features, the number of drones, and the parameters of the drones. In the second step, based on the routes obtained in the first step, the real-time movement of the drones was controlled during processing, including camera movement and image recording. The third step is post-processing, i.e., processing the images for QR code identification, interpreting the QR code, and recognizing empty compartments for inventory control. A major advantage for users of the solution method is that the result can be achieved automatically without an external orientation device, relying solely on its own movement and the organization of a pre-planned route. The proposed model and solution method are suitable not only for inventory control, but also for solving other problems matching the model.https://www.mdpi.com/2504-446X/6/11/364stock inventorydronegenetic algorithm |
| spellingShingle | Miklós Gubán József Udvaros A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones Drones stock inventory drone genetic algorithm |
| title | A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones |
| title_full | A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones |
| title_fullStr | A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones |
| title_full_unstemmed | A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones |
| title_short | A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones |
| title_sort | path planning model with a genetic algorithm for stock inventory using a swarm of drones |
| topic | stock inventory drone genetic algorithm |
| url | https://www.mdpi.com/2504-446X/6/11/364 |
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