期刊论文

Lv, Q

英文

Aerospace

2226-4310

2023

10

6

562-

10.3390/aerospace10060562

Conceptualization, G.H., Q.L. and Z.H.; methodology, G.H. and Q.L.; software, G.H.; validation, G.H., Q.L., H.Z. and W.C.; formal analysis, G.H. and H.Z.; investigation, G.H., Q.L., Z.H. and W.C; resources, G.H., Q.L., Z.H., H.Z. and W.C.; data curation, G.H. and Q.L.; funding acquisition, Z.H. All authors contributed equally to this work. All authors have read and agreed to the published version of the manuscript. The National Natural Science Foundation of China (Grant No. 61873101), the PetroChina Innovation Foundation (Grant No. 2020D-5007-0305), and the Marine Defense Technology Innovation Center Innovation Fund (Grant No. JJ-2020-719-03-02) supported this study.

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The obstacle avoidance system of a drone affects the quality of its flight path. The artificial potential field method can react quickly when facing obstacles; however, the traditional artificial potential field method lacks consideration of the position information between drones and obstacles during flight, issues including local minima, unreachable targets, and unreasonable obstacle avoidance techniques that lengthen flight times and consume more energy get encountered. Therefore, an improved artificial potential field method is proposed. First, a collision risk assessment mechanism was int...