A COMPREHENSIVE REVIEW OF GENERATIVE DESIGN APPLICATIONS IN UNMANNED AERIAL VEHICLES
DOI:
https://doi.org/10.11113/aej.v15.21286Keywords:
Generative design, unmanned aerial vehicles, Challenges of Generative designAbstract
The continuous progress in Unmanned Aerial Vehicles (UAVs) has spurred the exploration of novel design approaches to boost their effectiveness. Many drone configuration design methods have been used to enhance strength and reduce weight, such as topology optimization, high-modulus composite material, additive manufacturing, etc. One rapidly emerging technology with the potential to transform UAV design is generative design. This cutting-edge technology employs artificial intelligence to generate numerous design possibilities, assisting engineers in identifying optimal designs that align with precise requirements. Consequently, it has the potential to enhance UAV performance, efficiency, and cost-effectiveness significantly. This paper delves into various generative design approaches for drones, covering structural components, aerodynamics, energy efficiency, and payload distribution applications. Real-world case studies prove the benefits of integrating generative design into the UAV development process. These studies demonstrate the effectiveness of generative design and pave the way for significant advancements in UAV capabilities and applications, instilling confidence in its potential.
References
Al-Dosari, K., & Fetais, N. 2023. A new shift in implementing unmanned aerial vehicles (UAVs) in the safety and security of smart cities: a systematic literature review. Safety 9(3): 64. DOI: https://doi.org/10.3390/safety9030064
Mohsan, S. A. H., Othman, N. Q. H., Li, Y., Alsharif, M. H., & Khan, M. A. 2023. Unmanned aerial vehicles (UAVs): Practical aspects, applications, open challenges, security issues, and future trends. Intelligent Service Robotics, 16(1): 109-137. DOI: https://doi.org/10.1007/s11370-022-00452-4
Sun, K., Wang, W., Cheng, R., Liang, Y., Xie, H., Wang, J., & Zhang, M. 2024. Evolutionary generative design of supercritical airfoils: an automated approach driven by small data. Complex & Intelligent Systems, 10(1): 1167-1183. DOI: https://doi.org/10.1007/s40747-023-01214-0
Liu, G., Van Huynh, N., Du, H., Hoang, D. T., Niyato, D., Zhu, K. & Kim, D. I. 2024. Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities. arXiv preprint. DOI: https://doi.org/10.48550/arXiv.2402.18062
Liao, W., Lu, X., Fei, Y., Gu, Y., & Huang, Y. 2024. Generative AI design for building structures, Automation in Construction,157: 105187. DOI: 10.1016/j.autcon.2023.105187
Borg, K., Sahadevan, V., Singh, V., & Kotnik, T. 2024. Leveraging Generative Design for Industrial Layout Planning: SWOT Analysis Insights from a Practical Case of Papermill Layout Design, Advanced Engineering Informatics, 60: 102375. DOI: 10.1016/j.aei.2024.102375
Botyarov, M. 2023. Optimizing Designer Cognition Relative to Generative Design Methods, Doctoral dissertation, Colorado State University
Vajna, S. et al. 2005. The Autogenetic Design Theory: An evolutionary view of the design process, Journal of Engineering Design, 16 (4): 423-440. DOI:10.1080/09544820500267781
Alison Mckay, M. C. A. H. H. C., & Pennington, A. D. 2006. Combining evolutionary algorithms and shape grammars to generate branded product design. In Design computing and cognition’o6, 521-539. Dordrecht: Springer Netherlands.
Krish, S. 2011. A practical generative design method, Computer-Aided Design, 43(1): 88-100. DOI: https://doi.org/10.1016/j.cad.2010.09.009
Barros, M., Duarte, J. P., & Chaparro, B. M. 2014. Integrated generative design tools for the mass customization of furniture. In Design Computing and Cognition'12, 285-300. Dordrecht: Springer Netherlands, DOI: 10.1007/978-94-017-9112-0_16
Chen, X. Anthony et al. 2018. Forte: User-Driven Generative Design, Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM Press, New York, USA, 1-12. DOI: https://doi.org/10.1145/3173574.3174070
Kazi, R.H. et al. 2017. Dream Sketch: Early-Stage 3D Design Explorations with Sketching and Generative Design. Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology - UIST ’17, ACM Press, New York, USA, 401-414. DOI: https://doi.org/10.1145/3126594.3126662
Jia, H. et al. 2011. Evolutionary level set method for structural topology optimization, Computers and Structures, 89(5-6): 445-454. DOI: 10.1016/j.compstruc.2010.11.003
Nordin, A. 2018. Challenges in the industrial implementation of generative design systems: An exploratory study. Artificial Intelligence for Engineering Design Analysis and Manufacturing, 32(1): 16-31. DOI: 10.1017/S0890060416000536
Tyflopoulos, E. et al. 2018. State of the art of generative design and topology optimization and potential research needs, DS 91: Proceedings of NordDesign, Linköping, Sweden, 14-17
Yu, Y., Wei, M., Cui, Y., Sun, B., Yu, Z., Xu, Q., & Wu, Y. 2024. Reliability-based topology-topography optimization for ship bulkhead structures considering multi-failure modes. Ocean Engineering, 293. DOI: http://dx.doi.org/10.2139/ssrn.4644192
Burnap, A., Liu, Y., Pan, Y., Lee, H., Gonzalez, R., & Papalambros, P. Y. 2016. Estimating and exploring the product form design space using deep generative models. In International design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical Engineers. DOI: 10.1115/DETC2016-60091
Oh, S., Jung, Y., Kim, S., Lee, I., & Kang, N. 2019. Deep generative design: Integration of topology optimization and generative models. Journal of Mechanical Design, 141(11). DOI: 10.1115/1.4044229
Oh, S., Jung, Y., Lee, I., & Kang, N. 2018. Design automation by integrating generative adversarial networks and topology optimization. In International design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical Engineers. DOI: 10.1115/DETC2018-85506
Khan, S., Gunpinar, E., & Sener, B. 2019. GenYacht: An interactive generative design system for computer-aided yacht hull design. Ocean Engineering, 191. DOI: 10.1016/j.oceaneng.2019.106462
Gunpinar, E., Coskun, U. C., Ozsipahi, M., & Gunpinar, S. 2019. A generative design and drag coefficient prediction system for sedan car side silhouettes based on computational fluid dynamics. Computer-Aided Design, 111: 65-79. DOI: 10.1016/j.cad.2019.02.003
Dogan, K. M., Suzuki, H., Gunpinar, E., & Kim, M. S. 2019. A generative sampling system for profile designs with shape constraints and user evaluation. Computer-Aided Design, 111: 93-112. DOI: 10.1016/j.cad.2019.02.002
Buonamici, F., Carfagni, M., Furferi, R., Volpe, Y., & Governi, L. 2020. Generative design: an explorative study. Computer-Aided Design and Applications, 18(1): 144-155. DOI: 10.14733/cadconfP.2020.6-10
Liao, J. Z. Z. L. J., Cao, Y. P., & Shan, Y. 2024. Advances in 3D Generation: A Survey. arXiv preprint. DOI: https://doi.org/10.48550/arXiv.2401.17807
Alhijawi, B., & Awajan. 2023. Genetic algorithms: Theory, genetic operators, solutions, and applications. Evolutionary Intelligence, 17(3), 1245-1256. DOI: 10.1007/s12065-023-00822-6
Gu, N.; Behbahani, P.A. 2018. Shape grammars: A key generative design algorithm. In Handbook of the Mathematics of the Arts and Sciences. 1–21. Springer Science and Business Media LLC: Berlin, Germany,
El-Maghraby, I. M., Jahin, H. M., & El-Hagla, K. S. 2023. Computational-based Generative Design Exploration, Multi-Agent System as an Approach. In Let It Grow, Let Us Plan, Let It Grow. Nature-based Solutions for Sustainable Resilient Smart Green and Blue Cities. Proceedings of REAL CORP, 28th International Conference on Urban Development, Regional Planning and Information Society, CORP–Competence Center of Urban and Regional Planning, 145-154.
Bailey, E. T., & Caldas, L. 2023. Operative generative design using non-dominated sorting genetic algorithm II (NSGA-II). Automation in Construction, 155, DOI: 10.1016/j.autcon.2023.105026
Caetano, I., Santos, L., & Leitão, A. 2020. Computational design in architecture: Defining parametric, generative, and algorithmic design. Frontiers of Architectural Research, 9(2): 287-300. DOI: 10.1016/j.foar.2019.12.008
Camba, J. D., Contero, M., & Company, P. 2016. Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design, 74: 18-31. DOI: 10.1016/j.cad.2016.01.003
Bhad, P. U., & Buktar, R. B. 2022. Multiple novel generative design solutions for various mechanical engineering related products using Autodesk Fusion 360 software. International Journal of Design Engineering, 11(1): 1-26. DOI: 10.1504/IJDE.2022.10051857
Goldstein, M. H., Sommer, J., Buswell, N. T., Li, X., Sha, Z., & Demirel, H. O. 2021. Uncovering generative design rationale in the undergraduate classroom. In 2021 IEEE Frontiers in Education Conference, 1-6. DOI: 10.1109/FIE49875.2021.9637365
Maricic, S., Haber, I. M., Veljovic, I., & Palunko, I. 2020. Implementation of optimum additive technologies design for unmanned aerial vehicle take-off weight increase. EUREKA: Physics and Engineering, (6): 50-60. DOI: https://doi.org/10.21303/2461-4262.2020.001514
Balayan, A.; Mallick, R.; Dwivedi, S.; Saxena, S.; Haorongbam, B.; Sharma, A. 2024. Optimal Design of Quadcopter Chassis Using Generative Design and Lightweight Materials to Advance Precision Agriculture. Machines, 12: 187. DOI: https:// doi.org/10.3390/machines12030187
Radakovic, D. 2021. Bridging Nature-Art-Engineering with Generative Design. In Experimental and Computational Investigations in Engineering: Proceedings of the International Conference of Experimental and Numerical Investigations and New Technologies, 326-343. Springer International Publishing,
Du Plessis, A., Broeckhoven, C., Yadroitsava, I., Yadroitsev, I., Hands, C. H., Kunju, R., & Bhate, D. 2019. Beautiful and functional: a review of biomimetic design in additive manufacturing. Additive Manufacturing, 27: 408-427. DOI: 10.1016/j.addma.2019.03.033
Mañé Ubalde, S. 2023. A study on the application of generative design in aircraft development, Master's thesis, Universitat Politècnica de Catalunya. http://hdl.handle.net/2117/403757
Nisar, M. M., Zia, S., Fenoon, M., & Alquabeh, O. 2021. Generative design of a mechanical pedal. International Journal of Engineering and Management Sciences, 6(1): 48-58. DOI: 10.21791/IJEMS.2021.1.5
Azeez, R. 2023. Generative design of a jet engine bracket using solid edge. Master degree of theses, Department of Mechanical Engineering, https://hdl.handle.net/2437/365151
Peckham, O., Elverum, C. W., Hicks, B., Goudswaard, M., Snider, C., Steinert, M., & Eikevåg, S. W. 2024. Investigating and Characterizing the Systemic Variability When Using Generative Design for Additive Manufacturing. Applied Sciences, 14(11): 4750. DOI: https://doi.org/10.3390/app14114750
Peraza-Garcia, J. 2024. Comparing and Contrasting the Merits of Additive Manufactured Electric Vehicle Suspension Components: GFR Case Study. Master’s Thesis, Mechanical Engineering. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/0v838860f
Ansari, A. A., & Kamil, M. 2021. Effect of print speed and extrusion temperature on properties of 3D printed PLA using fused deposition modeling process. Materials Today: Proceedings, 45: 5462-5468. DOI: 10.1016/j.matpr.2021.02.137
Czyba, R., Lemanowicz, M., Gorol, Z., & Kudala, T. 2018. Construction prototyping, flight dynamics modeling, and aerodynamic analysis of hybrid VTOL unmanned aircraft. Journal of Advanced Transportation, 1-15, DOI: 10.1155/2018/7040531
Shi, Z., Li, H., Lin, H., & Huang, L. 2018. A nano-quadcopter formation flight system based on UWB indoor positioning technology. In 2018 13th International Conference on Computer Science & Education, 1-4. DOI: 10.1109/ICCSE.2018.8468720
Zhang,W.; Li, G.; Baker, C. 2019. Dictionary Learning for Radar Classification of Multiple Micro-Drones. In Proceedings of the 2019 International Radar Conference (RADAR), Toulon, France, 1–4. DOI: 10.1109/RADAR41533.2019.171299
Mammarella, M., Capello, E., Dabbene, F., & Guglieri, G. 2018. Sample-based SMPC for tracking control of fixed-wing UAV. Institute of Electrical and Electronics Engineers control systems letters, 2(4): 611-616. DOI: 10.48550/arXiv.1805.05879
Zhang, N.; Zhou, X.; Zhang, J.; Huang, L.; Zhao, J. 2017. Developing a small UAV platform to detect sheath blight of rice. In Proceedings of the Institute of Electrical and Electronics Engineers International Geoscience and Remote Sensing Symposium, Fort Worth, USA, 23–28, 3190–3193.
Kurukularachchi, P.L.; Munasinghe, S.; De Silva, H. 2016. Stability analysis for a twin boom H- tail Medium Scale UAV through simulated dynamic model. In Proceedings of the 2016 Moratuwa Engineering Research Conference, Moratuwa, Sri Lanka, 415–420. DOI: 10.1109/MERCon.2016.7480177
Yi, W.; Liming, C.; LingYu, K.; Jie, Z.; Miao, W. 2017. Research on application mode of large fixed-wing UAV system on overhead transmission line. In Proceedings of the IEEE International Conference on Unmanned Systems (ICUS), Beijing, China, 88–91.
S. Souvanhnakhoomman, S. 2024. Review on application of drone in spraying pesticides and fertilizers. arXiv preprint. https://doi.org/10.48550/arXiv.2402.00020
Pfeifer, C.; Barbosa, A.; Mustafa, O.; Peter, H.-U.; Brenning, A.; Rümmler, M. 2019. Using Fixed-Wing UAV for Detecting and Mapping the Distribution and Abundance of Penguins on the South Shetlands Islands, Antarctica. Drones, 3: 39. DOI: 10.3390/drones3020039
Sun, K., Wang, W., Cheng, R., Liang, Y., Xie, H., Wang, J., & Zhang, M. 2024. Evolutionary generative design of supercritical airfoils: an automated approach driven by small data. Complex & Intelligent Systems, 10(1): 1167-1183. DOI: 10.1007/s40747-023-01214-0
Yeh, S. T., & Du, X. 2024. Transfer-Learning-Enhanced Regression Generative Adversarial Networks for Optimal eVTOL Takeoff Trajectory Prediction. Electronics, 13(10): 1911. DOI: https://doi.org/10.3390/electronics13101911
Li, B.; Zhou,W.; Sun, J.;Wen, C.-Y.; Chen, C.-K. 2021. Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight. Sensors, 18(9), 2859. DOI: https://doi.org/10.3390/s18092859
Olejnik, A.; Kiszkowiak, Ł.; Rogólski, R.; Chmaj, G.; Radomski, M.; Majcher, M.; Łukasz, O. 2020. The Use of Unmanned Aerial Vehicles in Remote Sensing Systems. Sensors, 20, DOI: 10.3390/s20072003
Hasan, A. F., Humaidi, A. J., Al-Obaidi, A. S. M., Azar, A. T., Ibraheem, I. K., Al-Dujaili, A. Q., ... & Abdulmajeed, F. A. 2023. Fractional order extended state observer enhances the performance of controlled tri-copter UAV based on active disturbance rejection control. In Mobile Robot: Motion Control and Path Planning, Springer International Publishing. 439-487. DOI: 10.1007/978-3-031-26564-8_14
Isnaini, I., Kusuma, F. A., & Simanjuntak, T. 2024. Design of quadcopter for radiation monitoring in nuclear region. In AIP Conference Proceedings, 2967(1). DOI: 10.1063/5.0192869
Shelare, S., Belkhode, P., Nikam, K. C., Yelamasetti, B., & Gajbhiye, T. 2023. A payload based detail study on design and simulation of hexacopter drone. International Journal on Interactive Design and Manufacturing , 1-18. DOI: 10.1007/s12008-023-01269-w
Aliverdi, A., & Aliverdi, A. 2024. Increased outlet design of flat-fan nozzle improves octocopter unmanned aerial vehicle sprayer's efficiency. Crop Protection, 182, 106736. DOI: 10.1016/j.cropro.2024.106736
Balayan, A., Mallick, R., Dwivedi, S., Saxena, S., Haorongbam, B., & Sharma, A. 2024. Optimal Design of Quadcopter Chassis Using Generative Design and Lightweight Materials to Advance Precision Agriculture. Machines, 12(3), 187. DOI: https://doi.org/10.3390/machines12030187
Arockiadoss, A. S., Novah, R. N., Sajal, K. S., Pratap, S. S., Premachandra, C., & Schilberg, D. 2024. Optimization of Monocoque Drone Frame Using Generative Design. In 2024 International Conference on Image Processing and Robotics, 1-6. DOI: 10.1109/ICIPRoB62548.2024.10543948
Ghazali, M. H. M., Azmin, A., & Rahiman, W. 2022. Drone implementation in precision agriculture–A survey. International Journal of Emerging Technology and Advanced Engineering, 12(4), 67-77. DOI: 10.46338/ijetae0422_10
Dhurjad, S., Shaikh, A., & Chinchanikar, S. 2023. Generative design for additive manufacturing (G-DFAM): An explorative study of aerospace brackets. In AIP Conference Proceedings, 2492(1). DOI: 10.1063/5.0113328
Gutierrez, S., Ocampo, J., & Narváez, C. A. 2023. Topological Optimization, Generative Design and Validation of Drone Structures. In AIAA SCITECH 2023 Forum, DOI: 10.2514/6.2023-0964
Seregi, B. L., & Ficzere, P. 2021. Weight Reduction of a Drone Using Generative Design. Hungarian Journal of Industry and Chemistry, 49(2), 19-22. DOI: 10.33927/hjic-2021-16
Bright, J., Suryaprakash, R., & Akash, S. 2021. Optimization of quadcopter frame using generative design and comparison with DJI F450 drone frame. In IOP Conference Series: Materials Science and Engineering, 1012(1). DOI: 10.1088/1757-899X/1012/1/012019
MohamedZain, A. O., Chua, H., & Yap, K. 2022. Novel Drone Design Using an Optimization Software with 3D Model, Simulation, and Fabrication in Drone Systems Research. Drones, 6(4), 97. DOI: 10.3390/drones6040097
Ghazaly, M. M., Jun, K. T., & Abdullah, Z. 2022. Analysis of a 6-axis drone weight optimization using generative design. Proceedings of Mechanical Engineering Research Day, 213-215. DOI: 10.30880/ijie.2023.15.04.009
Pilagatti, A. N., Vecchi, G., & Atzeni, E. 2022. Generative Design and new designers’ role in the manufacturing industry. Procedia CIRP, 112, 364-369. DOI: 10.1016/j.procir.2022.09.010
Marino, S. O. 2023. Generative Design for 3D Printing of Advanced Aerial Drones, Doctoral dissertation, Toronto Metropolitan University.
Gupta, A., Soni, V., Shah, D. and Lakdawala, A., 2023. Generative design of main landing gear for a remote-controlled aircraft. Materials. DOI: 10.1016/j.matpr.2023.01.380
Paz, J. D. S., & Bustamante, A. A. P. 2022. Applicability of Generative Design in the Construction of UAVs. In 2022 7th International Conference on Control and Robotics Engineering, 106-110. DOI: 10.1109/ICCRE55123.2022.9770256
Zaimis, I., Giannakis, E., & Savaidis, G. 2021. Generative design case study of a CNC machined nose landing gear for an unmanned aerial vehicle. In IOP Conference Series: Materials Science and Engineering, 1024(1). DOI: 10.1088/1757-899X/1024/1/012064
Srawanee, S., & Rao, M. S. 2023. Generative design and analysis of Quadcopter monobloc. Industrial Engineering Journal, 52(5).
“Product Design and Development” [Online]. Available: https://www.mheducation.com/highered/product/Product Design-and-Development-7-Ulrich.html. [Accessed: 20-June-2024].
Wang, Y. C., Xue, J., Wei, C., & Kuo, C. C. J. 2023. An overview on generative ai at scale with edge-cloud computing. IEEE Open Journal of the Communications Society. DOI: 10.1109/OJCOMS.2023.3320646
Ji, B. X., Liu, H. H., Cheng, P., Ren, X. Y., Pi, H. D., & Li, L. L. 2024. Phased optimization of active distribution networks incorporating distributed photovoltaic storage system: A multi-objective coati optimization algorithm. Journal of Energy Storage, 91: 112093. DOI: 10.1016/j.est.2024.112093
“Design Computing: An Overview of an Emergent Field” [Online]. Available: https://www.routledge.com/Design-Computing-An-Overview-of-an-Emergent-Field. [Accessed: 21-June-2024].
“The Next Wave of Intelligent Design Automation” [Online]. Available: https://hbr.org/sponsored/2018/06/thenext-wave-of-intelligent-design-automation. [Accessed on 19 Sep 2023]
Dean, L., & Loy, J. 2020. Generative product design futures. The Design Journal, 23(3): 331-349. DOI: 10.1080/14606925.2020.1745569
Lowry, P. B., Moody, G. D., Parameswaran, S., & Brown, N. J. 2023. Examining the differential effectiveness of fear appeals in information security management using two-stage meta-analysis. Journal of Management Information Systems, 40(4), 1099-1138. DOI: 10.1080/07421222.2023.2267318
Kallioras, N.A.; Lagaros, N.D. DzAIN. 2020. Deep learning based generative design. Procedia Manufacturing 44: 591–598. DOI: 10.1016/j.promfg.2020.02.251
Jagtap, S. 2019. Design creativity: Refined method for novelty assessment. International Journal of Design Creativity and Innovation, 7(1-2): 99-115. DOI: 10.1080/21650349.2018.1463176
