Abstract
The rapid growth of network systems in the current scenario requires information efficacy and transmission speed, which is a very big challenge in Unmanned Aerial Vehicle (UAV) networks. The accuracy of data and the speed of transferring information should work hand in hand without any flaws. The participation of UAVs in the applications like surveillance, security, surveying, and emergency response in rescue operations has changed the dimension of expectations from users on the subject of their efficiency and speed. Recently the process of gathering data from such applications by using machines like drones and robots became quite common. A drone can be pilot driven or autonomous where in the latter case the complexity increases in designing the system. Another discrepancy in the usage of autonomous drones is the battery power’s durability. The solution to overcome the problem is to optimize the path which will enhance the longevity of the battery. In this paper, we propose a priority path planning algorithm to achieve path optimization faster. This is achieved by two sequences of operations. A grid map is generated with occupancy values in each cell which estimates the distance to be traveled by the drone based on the input map fed by the user for the known path. The second process is to trace the shortest path from all possible routes. Third is the security and smoothness of operation. The first two techniques can be combined and called path planning. The techniques inhibited in this paper are analyzed in such a way it is useful for surveillance and surveying where the path of the drone to be traveled is known and the area to be covered is also predetermined. The simulation results and comparison charts show that the proposed algorithm is better compared to existing techniques like fuzzy logic, ant colony optimization, and particle swarm optimization techniques.
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References
Koushik AM, Hu F, Kumar S (2019) Deep ${Q} $-learning-based node positioning for throughput-optimal communications in dynamic UAV swarm network. IEEE Trans Cognit Commun Network 5(3):554–566
El Hammouti H, Benjillali M, Shihada B, Alouini M-S (2019) Learn-as-you-fly: a distributed algorithm for joint 3D placement and user association in multi-UAVs networks. IEEE Trans Wireless Commun 18(12):5831–5844
Aljehani M, Inoue M (2019) Performance evaluation of multi-UAV system in post-disaster application: validated by HITL simulator. IEEE Access 7:64386–64400
Morita T, Oyama K, Mikoshi T, Nishizono T (2018) Decision making support of UAV path planning for efficient sensing in radiation dose mapping. In: 2018 IEEE 42nd annual computer software and applications conference (COMPSAC) 1:333–338)
Sizkouhi AM, Esmailifar SM, Aghaei M, De Oliveira AK, Rüther R (2019) Autonomous path planning by unmanned aerial vehicle (UAV) for precise monitoring of large-scale PV plants. In: 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) pp. 1398–1402
Wang Y, Bai P, Liang X, Wang Weijia, Zhang Jiaqiang, Fu Qixi (2019) Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms. IEEE Access 7:105086–105099
Na HJ, Yoo SJ (2019) PSO-based dynamic UAV positioning algorithm for sensing information acquisition in wireless sensor networks. IEEE Access 7:77499–77513
Venkatasivarambabu P, Agrawal R (2024) Enhancing UAV navigation with dynamic programming and hybrid probabilistic route mapping: an improved dynamic window approach. Int J Inf Tecnol 16:1023–1032
Marwah N, Singh VK, Kashyap GS et al (2023) An analysis of the robustness of UAV agriculture field coverage using multi-agent reinforcement learning. Int J Inf Tecnol 15(2317–2327):6
Yan Chaoxing, Fu Lingang, Zhang Jiankang, Wang Jingjing (2019) A comprehensive survey on UAV communication channel modeling. IEEE Access 7:107769–107792
Baoping W, Jianjun M, Zhaoxuan H, Yan Z, Yang F, Yimeng G (2018) Adaptive image enhancement algorithm based on fuzzy entropy and human visual characteristics. J Syst Eng Electron 29(5):1079–1088
Wang Y, Bai P, Liang X, Wang W, Zhang J, Fu Q (2019) Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms. IEEE Access 7:105086–105099
Yasin JN, Mohamed SAS, Haghbayan MH et al (2021) Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots. Int J Inf Tecnol 13:97–107
Xiao C, Zou Y, Li S (2019) UAV multiple dynamic objects path planning in air-ground coordination using receding horizon strategy. In: 2019 3rd international symposium on autonomous systems (ISAS) (pp. 335–340)
Song Q, Zhao Q, Wang S, Liu Q, Chen X (2020) Dynamic path planning for unmanned vehicles based on fuzzy logic and improved ant colony optimization. IEEE Access 8:62107–62115
Guo J, Li C, Guo S (2019) A novel step optimal path planning algorithm for the spherical mobile robot based on fuzzy control. IEEE Access 8:1394–1405
Gupta V, Seth D (2024) 3Dimensional improvise clustering algorithm for unmanned aerial vehicles: 3DICA. Int J Inf Tecnol
Hanna S, Yan H, Cabric D (2019) Distributed UAV placement optimization for cooperative line-of-sight MIMO communications. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4619–4623)
Yuvaraj R, Sarveshwaran V (2024) Modified hunter prey optimization to enable secure communication for UAV. Int J Inf Tecnol 16:1569–1579
Hao H, Luo Y (2019) An original bionic algorithm: interdependent balance algorithm. In: 2019 IEEE 2nd international conference on electronic information and communication technology (ICEICT) (pp. 584–589)
Mi J, Wen X, Sun C, Lu Z, Jing W (2019) Energy-efficient and low package loss clustering in UAV-assisted WSN using Kmeans++ and fuzzy logic. In: 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops) (pp. 210–215)
Mahbub M (2021) Unmanned aerial vehicle-collaborative 5G: a cooperative technology for enhancement of 5G NR. Int J Inf Tecnol 13:793–799
Mukherjee A, Misra S, Chandra VSP, Obaidat MS (2019) Resource-optimized multiarmed bandit-based offload path selection in edge UAV swarms. IEEE Internet Things J 6(3):4889–4896
Zhang X, Ali M (2020) A bean optimization-based cooperation method for target searching by swarm UAVs in unknown environments. IEEE Access 8:43850–43862
Wang Y, Bai P, Liang X, Wang W, Zhang J, Fu Q (2019) Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms. IEEE Access 7:105086–105099
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Vijaya J, Meena Thangaraj: Software, Visualization, Investigation, Writing original draft, Supervision, Conceptualization, Methodology, Writing - review & editing, Data curation, Validation, Formal analysis.
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Vijaya, J., Thangaraj, M. Analysis and optimization of path finding algorithm for unmanned aerial vehicles. Int. j. inf. tecnol. (2024). https://doi.org/10.1007/s41870-024-01917-8
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DOI: https://doi.org/10.1007/s41870-024-01917-8