Abstract
Unmanned Aerial Vehicles (UAVs) have revolutionized various industries by offering innovative solutions for tasks ranging from surveillance to logistics. This chapter presents a comprehensive study on the development and deployment of a hovercraft UAV system tailored for efficient light part delivery within a manufacturing plant environment. The system leverages a combination of technologies including computer vision, electromagnetic tags, ultrasonic sensors, accelerometers, and gyroscopes for precise corridor navigation. The indoor localization aspect is addressed through the implementation of ArUco markers, fused with Ultra-wideband (UWB) tags. These visual markers enable the UAV to accurately determine its position and orientation in complex indoor settings. The integration of ultrasonic sensors enhances the system’s capability to detect obstacles, enabling real-time adjustments to the flight path to ensure safe and reliable navigation. Additionally, the incorporation of the MPU6050 sensor provides crucial feedback for corridor navigation, allowing the UAV to maintain stability and orientation while maneuvering through tight spaces. Results demonstrate the successful localization accuracy and the ability to operate within confined pathways, mitigating the risk of disruptions in the manufacturing plant environment. The outcomes of this research contribute to advancing UAV-assisted logistics and operations within industrial settings.
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References
Cook, K. L. (2007). The silent force multiplier: The history and role of UAVs in warfare. In 2007 IEEE Aerospace Conference (pp. 1–7). IEEE.
Fahlstrom, P. G., Gleason, T. J., & Sadraey, M. H. (2022). Introduction to UAV systems. Wiley.
Samad, A. M., Kamarulzaman, N., Hamdani, M. A., Mastor, T. A., & Hashim, K. A. (2013). The potential of unmanned aerial vehicle (UAV) for civilian and mapping application. In 2013 IEEE 3rd International Conference on System Engineering and Technology (pp. 313–318). IEEE.
Sharma, B., Obaidat, M. S., Sharma, V., & Hsiao, K. F. (2020). Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions. International Journal of Communication Systems, 33(18), e4628.
Bailon-Ruiz, R., & Lacroix, S. (2020). Wildfire remote sensing with UAVs: A review from the autonomy point of view. In 2020 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 412–420). IEEE.
Škrinjar, J. P., Škorput, P., & Furdić, M. (2019). Application of unmanned aerial vehicles in logistic processes. In New Technologies, Development and Application 4 (pp. 359–366). Springer International Publishing.
Estrada, M. A. R., & Ndoma, A. (2019). The uses of unmanned aerial vehicles–UAV’s-(or drones) in social logistic: Natural disasters response and humanitarian relief aid. Procedia Computer Science, 149, 375–383.
Gonzalez-R, P. L., Canca, D., Andrade-Pineda, J. L., Calle, M., & Leon-Blanco, J. M. (2020). Truck-drone team logistics: A heuristic approach to multi-drop route planning. Transportation Research Part C: Emerging Technologies, 114, 657–680.
Boysen, N., Fedtke, S., & Schwerdfeger, S. (2021). Last-mile delivery concepts: A survey from an operational research perspective. OR Spectrum, 43, 1–58.
Das, D. N., Sewani, R., Wang, J., & Tiwari, M. K. (2020). Synchronized truck and drone routing in package delivery logistics. IEEE Transactions on Intelligent Transportation Systems, 22(9), 5772–5782.
Sun, Y., Xu, J., Qiang, H., & Lin, G. (2019). Adaptive neural-fuzzy robust position control scheme for maglev train systems with experimental verification. IEEE Transactions on Industrial Electronics, 66(11), 8589–8599.
Kunze, O. (2016). Replicators, ground drones and crowd logistics a vision of urban logistics in the year 2030. Transportation Research Procedia, 19, 286–299.
Detweiler, C., Griffin, B., & Roehr, H. (2012). Omni-directional hovercraft design as a foundation for MAV education. In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 786–792). IEEE.
Parker, S. (2007). The LCAC military hovercraft. Capstone.
Hollebone, A. (2012). The hovercraft: A history. The History Press.
Toyama, Y., Ono, S., & Nishihara, S. (1992). Design of hovercraft skirt system water scoop by rear skirts and practical solution. Journal of the Society of Naval Architects of Japan, 1992(172), 383–391.
Pavăl, M. S., Popescu, A., & Zahariea, D. (2019). Numerical analysis of the influence of the lower hull angle of a round skirtless air cushion vehicle. In IOP Conference Series: Materials Science and Engineering (Vol. 595, No. 1, p. 012049). IOP Publishing.
Rothwell, R., & Gardiner, P. (1985). Invention, innovation, re-innovation and the role of the user: A case study of British hovercraft development. Technovation, 3(3), 167–186.
Tiemann, J., Schweikowski, F., & Wietfeld, C. (2015). Design of an UWB indoor-positioning system for UAV navigation in GNSS-denied environments. In 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1–7). IEEE.
Alarifi, A., Al-Salman, A., Alsaleh, M., Alnafessah, A., Al-Hadhrami, S., Al-Ammar, M. A., & Al-Khalifa, H. S. (2016). Ultra wideband indoor positioning technologies: Analysis and recent advances. Sensors, 16(5), 707.
Rezwan, S., & Choi, W. (2022). Artificial intelligence approaches for UAV navigation: Recent advances and future challenges. IEEE Access, 10, 26320–26339.
Cesetti, A., Frontoni, E., Mancini, A., Zingaretti, P., & Longhi, S. (2010). A vision-based guidance system for UAV navigation and safe landing using natural landmarks. Journal of Intelligent and Robotic Systems, 57, 233–257.
Romero-Ramirez, F. J., Muñoz-Salinas, R., & Medina-Carnicer, R. (2018). Speeded up detection of squared fiducial markers. Image and Vision Computing, 76, 38–47.
Garrido-Jurado, S., Munoz-Salinas, R., Madrid-Cuevas, F. J., & Medina-Carnicer, R. (2016). Generation of fiducial marker dictionaries using mixed integer linear programming. Pattern Recognition, 51, 481–491.
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Orgeira-Crespo, P., Rey, G., Pousada, P.R., Aguado-Agelet, F. (2024). Transport of Light Parts for Logistics Supply in Industrial Manufacturing Plants by Means of UAV. In: Carou, D., Sartal, A., Davim, J.P. (eds) Applying Drones to Current Societal and Industrial Challenges. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-55571-8_6
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