Autonomous Path Planning of Unmanned Air Systems Using Computational Methods and Optimization Algorithm

Islam, Tausiful; Tanvin, Jahiduzzaman; Hasan, Muhammad Samin

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dc.contributor.author	Islam, Tausiful
dc.contributor.author	Tanvin, Jahiduzzaman
dc.contributor.author	Hasan, Muhammad Samin
dc.date.accessioned	2023-03-10T07:07:51Z
dc.date.available	2023-03-10T07:07:51Z
dc.date.issued	2022-05-30
dc.identifier.citation	[1] What is the difference between a drone and an RC plane or helicopter? Drones Etc. [2] P. Drones, “The Differences Between UAV, UAS, and Autonomous Drones,” Percepto, Jan. 2019, Accessed: May 10, 2022. [Online]. Available: https://percepto.co/what-are-the-differences-between-uav-uas-and-autonomousdrones/. [3] State government gears up for autonomous RPAS mapping. 2017. [4] “Automated Drone (UAV) Applications \| Airobotics.” https://www.airoboticsdrones.com/applications/?fbclid=IwAR3js5BgRyVHUp_Y M_9Cc-OVdPAu1JEvkCazDrtjHTxAjRS4TlceLrfbEgA (accessed May 10, 2022). [5] B. Vergouw, H. Nagel, G. Bondt, and B. Custers, “Drone Technology: Types, Payloads, Applications, Frequency Spectrum Issues and Future Developments,” Futur. Drone Use Oppor. Threat. from Ethical Leg. Perspect., pp. 21–45, 2016, doi: 10.1007/978-94-6265-132-6_2. [6] V. K. Saxena, “The Amazing Growth and Journey of UAV’s and Ballastic Missile Defence Capabilities: Where the Technology is Leading to?,” p. 6, 2013, Accessed: May 10, 2022. [Online]. Available: https://books.google.com/books?id=hwWqCQAAQBAJ&pg=PA6. [7] “Applications and Uses for Multirotor Drones – Rise Above.” https://riseabove.com.au/pages/uav-applications-anduses?fbclid=IwAR3nnGS4YuIJZDNwC3Czbkuw5W52gKXVIelDgBgo4cenMOS dBeNKxi1Dj-M (accessed May 10, 2022). [8] “11. Optimization Algorithms — Dive into Deep Learning 0.17.5 documentation.” https://d2l.ai/chapter_optimization/?fbclid=IwAR2jM2LqOMf8zWpD7Xdbrq6Dmjqr1XOkBaz1alE-yY-_Vi92YkCb-MaPZA (accessed May 10, 2022). 68 [9] R. Jarray, M. Al-Dhaifallah, H. Rezk, and S. Bouallegue, “Path Planning of Quadrotors in a Dynamic Environment Using a Multicriteria Multi-Verse Optimizer,” C. Mater. Contin., vol. 69, no. 2, pp. 2159–2180, 2021. [10] C. Ramirez-Atencia and D. Camacho, “Constrained multi-objective optimization for multi-UAV planning,” J. Ambient Intell. Humaniz. Comput., vol. 10, no. 6, pp. 2467–2484, 2019. [11] S. Hayat, E. Yanmaz, T. X. Brown, and C. Bettstetter, “Multi-objective UAV path planning for search and rescue,” in 2017 IEEE international conference on robotics and automation (ICRA), 2017, pp. 5569–5574. [12] L. Swartzentruber, J. L. Foo, and E. Winer, “Three-dimensional multi-objective UAV path planner using terrain information,” in 50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 17th AIAA/ASME/AHS Adaptive Structures Conference 11th AIAA No, 2009, p. 2222. [13] S. Mittal and K. Deb, “Three-dimensional offline path planning for UAVs using multiobjective evolutionary algorithms,” in 2007 IEEE Congress on Evolutionary Computation, 2007, pp. 3195–3202. [14] D. Rathbun, S. Kragelund, A. Pongpunwattana, and B. Capozzi, “An evolution based path planning algorithm for autonomous motion of a UAV through uncertain environments,” in Proceedings. The 21st Digital Avionics Systems Conference, 2002, vol. 2, pp. 8D2-8D2. [15] S. Aggarwal and N. Kumar, “Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges,” Comput. Commun., vol. 149, pp. 270–299, 2020. [16] R. D’Andrea, “Guest editorial can drones deliver?,” IEEE Trans. Autom. Sci. Eng., vol. 11, no. 3, pp. 647–648, 2014. [17] K. Dorling, J. Heinrichs, G. G. Messier, and S. Magierowski, “Vehicle routing problems for drone delivery,” IEEE Trans. Syst. Man, Cybern. Syst., vol. 47, no. 1, 69 pp. 70–85, 2016. [18] H. Y. Jeong, B. D. Song, and S. Lee, “Truck-drone hybrid delivery routing: Payload-energy dependency and No-Fly zones,” Int. J. Prod. Econ., vol. 214, pp. 220–233, 2019. [19] C.-M. Tseng, C.-K. Chau, K. M. Elbassioni, and M. Khonji, “Flight tour planning with recharging optimization for battery-operated autonomous drones,” CoRR, abs/1703.10049, 2017. [20] J. Zhang, J. F. Campbell, D. C. Sweeney II, and A. C. Hupman, “Energy consumption models for delivery drones: A comparison and assessment,” Transp. Res. Part D Transp. Environ., vol. 90, p. 102668, 2021. [21] E. Kim, J. Lee, and K. G. Shin, “Real-time prediction of battery power requirements for electric vehicles,” in 2013 ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2013, pp. 11–20. [22] A. Cappiello, I. Chabini, E. K. Nam, A. Lue, and M. Abou Zeid, “A statistical model of vehicle emissions and fuel consumption,” in Proceedings. The IEEE 5th international conference on intelligent transportation systems, 2002, pp. 801–809. [23] K. I. M. McKinnon, “Convergence of the Nelder–Mead simplex method to a nonstationary point,” SIAM J. Optim., vol. 9, no. 1, pp. 148–158, 1999, doi: 10.1137/S1052623496303482. [24] M. A. Luersen and R. Le Riche, “Globalized Nelder–Mead method for engineering optimization,” Comput. Struct., vol. 82, no. 23–26, pp. 2251–2260, 2004. [25] R. Chelouah and P. Siarry, “Genetic and Nelder–Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions,” Eur. J. Oper. Res., vol. 148, no. 2, pp. 335–348, 2003. [26] S. Berezina, O. Solonets, and M. Bortsova, “Referencing of UAV Images Using the Nelder-Mead Method,” in 2018 IEEE 17th International Conference on Mathematical Methods in Electromagnetic Theory (MMET), 2018, pp. 103–106. 70 [27] R. C. Eberhart, Y. Shi, and J. Kennedy, Swarm intelligence. Elsevier, 2001. [28] D. Karaboga and B. Akay, “A survey: algorithms simulating bee swarm intelligence,” Artif. Intell. Rev., vol. 31, no. 1, pp. 61–85, 2009. [29] A. Akhtar, “Evolution of Ant Colony Optimization Algorithm--A Brief Literature Review,” arXiv Prepr. arXiv1908.08007, 2019. [30] K. Socha and M. Dorigo, “Ant colony optimization for continuous domains,” Eur. J. Oper. Res., vol. 185, no. 3, pp. 1155–1173, 2008. [31] “What Are Autonomous Drones? How Do They Work? - Remoteflyer.” https://www.remoteflyer.com/what-are-autonomous-drones-how-do-they-work/ (accessed May 17, 2022). [32] “Autonomous Drone Using RPi : 9 Steps - Instructables.” https://www.instructables.com/Autonomous-Drone-Using-RPi/ (accessed May 17, 2022). [33] “Copter Home — Copter documentation.” https://ardupilot.org/copter/ (accessed May 17, 2022). [34] “First Flight with Copter — Copter documentation.” https://ardupilot.org/copter/docs/flying-arducopter.html (accessed May 17, 2022). [35] H. Gossett, “Building An Autonomous Indoor Drone System,” 2018. [36] “DroneKit.” https://dronekit.io/ (accessed May 17, 2022). [37] “What is Cost Function in Machine Learning [Updated] \| Simplilearn.” https://www.simplilearn.com/tutorials/machine-learning-tutorial/cost-function-inmachine-learning (accessed May 10, 2022). [38] D. Brescianini, M. Hehn, and R. D’Andrea, “Nonlinear quadrocopter attitude control: Technical report,” ETH Zurich, 2013. [39] “Pixhawk Overview — Copter documentation.” https://ardupilot.org/copter/docs/common-pixhawk-overview.html (accessed May 17, 2022). 71 [40] J. Lesko, M. Schreiner, D. Megyesi, and L. Kovacs, “Pixhawk PX-4 Autopilot in Control of a Small Unmanned Airplane,” 2019 Mod. Saf. Technol. Transp., pp. 90–93, Nov. 2019, doi: 10.1109/MOSATT48908.2019.8944101. [41] “How to Choose an Optimization Algorithm.” https://machinelearningmastery.com/tour-of-optimizationalgorithms/?fbclid=IwAR0EA6_TcpbDuJrNXYwNbXiSBiZ_n4UAveVvJ5Q2LV M0OcC-sJf7Y7pZGUY (accessed May 10, 2022).	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/1753
dc.description	Supervised by Dr. Mohammad Ahsan Habib Professor Department of Mechanical & Production Engineering (MPE) Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Mechanical and Production Engineering, 2022.	en_US
dc.description.abstract	In recent years, the use of Unmanned Air Systems (UAS) has become popular in many industries including agriculture, logistics, security agencies and humanitarian missions. An Unmanned Air System consists of a drone or Unmanned Aircraft (UA) connected to the Ground Control Station (GCS) via various means of communication. During the early stages of development, most of these UAs were remotely operated by a pilot. However, various modes of autonomy are added nowadays to make way for autonomous flights. This allows the systems to be implemented in long haul flights, specifically in the realm of parcel delivery and humanitarian aid missions. To perform these missions, path planning is required since there is a multitude of paths that the UA can follow in order to reach its destination. The paths may vary in terms of distance, environmental parameters including wind speed and temperature, potential danger zones and so on. In order to minimize the costs of the user and to ensure the success of the mission, the operator has to select the best possible path for the flight. Since the problem comprises a lot of variables, a multiobjective function may be devised to help with the selection process. This paper explores the use of a custom-made cost function which is used to check the usefulness of a set path. The cost function takes into account the distance, time of completion and the energy consumption of the path to come up with a score for that specific path. The start and end points of the journey are fed to the system and an optimization algorithm is used with the custom-made cost function to derive the optimum path for the UA to complete the mission. The process is run for an array of environments, each with a different start and end point, and the optimized path is fed to the UA. The UA then actually flies through this route and the results of the actual flight are compared to the results obtained from the theoretical process to ensure that there is harmony between them.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT)	en_US
dc.subject	UAV, Optimization Algorithm, Autonomous Path Planning	en_US
dc.title	Autonomous Path Planning of Unmanned Air Systems Using Computational Methods and Optimization Algorithm	en_US
dc.type	Thesis	en_US