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Jinxiong Gao, Xu Geng, Yonghui Zhang and Jingbo Wang
Underwater autonomous path planning is a critical component of intelligent underwater vehicle system design, especially for maritime conservation and monitoring missions. Effective path planning for these robots necessitates considering various constrain...
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Yicong Guo, Xiaoxiong Liu, Xuhang Liu, Yue Yang and Weiguo Zhang
In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending the sta...
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Yi-Ju Tsai, Chia-Sung Lee, Chun-Liang Lin and Ching-Huei Huang
This study addresses the flight-path planning problem for multirotor aerial vehicles (AVs). We consider the specific features and requirements of real-time flight-path planning and develop a rapidly-exploring random tree (RRT) algorithm to determine a pr...
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