2021
DOI: 10.11591/ijeecs.v24.i2.pp1017-1026
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Review on path planning algorithm for unmanned aerial vehicles

Abstract: The path planning problem has been a crucial topic to be solved in autonomous vehicles. Path planning consists operations to find the route that passes through all of the points of interest in a given area. Several algorithms have been proposed and outlined in the various literature for the path planning of autonomous vehicle especially for unmanned aerial vehicles (UAV). The algorithms are not guaranteed to give full performance in each path planning cases but each one of them has their own specification whic… Show more

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Cited by 8 publications
(6 citation statements)
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“…However, this algorithm is not practical in a dynamic environment. To overcome this, the D* algorithm and its variants, as reviewed in [ 48 ], are efficient tools for quick re-planning in a cluttered environment. The D* algorithm updates the cost of new nodes, allowing the use of prior paths instead of re-planning the entire path.…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, this algorithm is not practical in a dynamic environment. To overcome this, the D* algorithm and its variants, as reviewed in [ 48 ], are efficient tools for quick re-planning in a cluttered environment. The D* algorithm updates the cost of new nodes, allowing the use of prior paths instead of re-planning the entire path.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In addition, this algorithm is conceptually simple and very easy to implement. Although the algorithm can achieve probabilistic completeness, it is not guaranteed to reach optimality [32]. Also, the execution time and increased computation time with an unknown convergence rate can cause problems.…”
Section: Rapid-exploring Random Treesmentioning
confidence: 99%
“…While this algorithm takes into account both static and dynamic threats, it uses an artificial field to simulate the environment for collision-free PP for the UAV. Hao and Xu [47] integrated immune network optimization with ACO to improve the shortest path finding capability of a multi-UAV system for PP [32].…”
Section: Ant Colony Optimizationmentioning
confidence: 99%
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“…Also [15], presented the latest algorithms for path planning of UAVs in both known and unknown environments. [16,17] Summarized the better understanding on the algorithms and described briefly the advantages and disadvantages of each algorithm. Moreover, in order to determine an optimal or near-optimal path [18], provided an overview of popular techniques recommended for UAVs navigation in an environment and path planning algorithms recommended for UAVs.…”
Section: Introductionmentioning
confidence: 99%