2021
DOI: 10.3390/s21155250
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Complex Environment Path Planning for Unmanned Aerial Vehicles

Abstract: Flying safely in complex urban environments is a challenge for unmanned aerial vehicles because path planning in urban environments with many narrow passages and few dynamic flight obstacles is difficult. The path planning problem is decomposed into global path planning and local path adjustment in this paper. First, a branch-selected rapidly-exploring random tree (BS-RRT) algorithm is proposed to solve the global path planning problem in environments with narrow passages. A cyclic pruning algorithm is propose… Show more

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Cited by 15 publications
(12 citation statements)
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“…Robot technology also originated in the United States. At present, the performance of robots studied in the United States is still at the forefront of the industry [7]. Many soldiers in the United States are physically disabled and unable to walk normally due to their participation in the war, which seriously affects their daily life.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Robot technology also originated in the United States. At present, the performance of robots studied in the United States is still at the forefront of the industry [7]. Many soldiers in the United States are physically disabled and unable to walk normally due to their participation in the war, which seriously affects their daily life.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Huang and Zhang [6,7] improved the defects of genetic algorithm and RRT algorithm respectively, and proposed an improved UAV path planning algorithm. Zhang [8] established an objective function based on the minimum flight time, battery energy consumption, and risk of drones, and studied the drone navigation planning between two freight warehouses in urban areas. Yang [9] studied the path planning scheme of mobile robot considering path obstacle avoidance.…”
Section: Introductionmentioning
confidence: 99%
“…Zhang et al proposed a branch selection rapid exploration random tree (BS-RRT) algorithm to solve the global path planning problem in the narrow channel environment of UAVs. However, these two algorithms are aimed at aerial unmanned equipment, which is not the same as the background of this study [ 26 ]. Yu et al combined the improved Grey Wolf Optimization algorithm with the Light algorithm and proposed a multi-target path planning algorithm for an unmanned cruise ship in an unknown obstacle environment [ 27 ].…”
Section: Introductionmentioning
confidence: 99%