期刊
SENSORS
卷 19, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/s19081758
关键词
UAVs; path planning; obstacle avoidance; MTS; optimization algorithms
资金
- National Natural Science Foundation of China [61401385, 61702146]
- Hong Kong Research Grants Council Early Career Scheme [25214015]
- Departmental General Research Fund of Hong Kong Polytechnic University [G.61.37.UA7L]
- PolyU Central Research Grant [G-YBMU]
Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.
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