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An Efficient Approach Toward Path Planning for Unmanned Aerial Vehicles (UAVs)

Deilam Salehi, Emad | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56244 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Fazli, Mohammad Amin
  7. Abstract:
  8. Path planning is essential for unmanned aerial vehicles (UAVs) to navigate complex and hazardous environments. Many algorithms have been proposed to solve this problem, but heuristic, meta-heuristic, and hybrid algorithms have recently gained attention due to their ability to find approximate solutions quickly. In this thesis, we propose using the Late Acceptance Hill Climbing (LAHC) algorithm for UAV path planning. We compare LAHC's performance to classical and state-of-the-art optimization algorithms, including simulated annealing (SA), grey wolf optimization (GWO), symbiotic organisms search (SOS), and simplified grey wolf optimizer-modified symbiotic organisms search (SGWO-MSOS). Simulations are conducted in both 2D and 3D environments, and in three different flying environments with varying levels of complexity. The results show that LAHC outperforms the other algorithms in terms of path cost, number of iterations to convergence, and average execution time. Moreover, in the rare cases where the novel SGWO-MSOS algorithm generates a path similar to our proposed algorithm, LAHC has the advantage of requiring significantly less computational time to produce the same path. Additionally, we perform a convergence and complexity analysis of the LAHC algorithm. Overall, the findings suggest that LAHC is a promising algorithm for UAV path planning in complex and hazardous environments
  9. Keywords:
  10. Routing ; Unmanned Aircrafts ; Heuristic Algorithm ; Meta Heuristic Algorithm ; Unmanned Aerial Vehicles (UAV) ; Hybrid Algorithm ; Gray Wolf Algorithm

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