Safety-enhanced UAV path planning with spherical vector-based particle swarm optimization

نویسندگان

چکیده

This paper presents a new algorithm named spherical vector-based particle swarm optimization (SPSO) to deal with the problem of path planning for unmanned aerial vehicles (UAVs) in complicated environments subjected multiple threats. A cost function is first formulated convert into an that incorporates requirements and constraints feasible safe operation UAV. SPSO then used find optimal minimizes by efficiently searching configuration space UAV via correspondence between position speed, turn angle climb/dive To evaluate performance SPSO, eight benchmarking scenarios have been generated from real digital elevation model maps. The results show proposed outperforms not only other (PSO) variants including classic PSO, phase angle-encoded PSO quantum-behave but also state-of-the-art metaheuristic algorithms genetic (GA), artificial bee colony (ABC), differential evolution (DE) most scenarios. In addition, experiments conducted demonstrate validity paths operations. Source code can be found at https://github.com/duongpm/SPSO.

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ژورنال

عنوان ژورنال: Applied Soft Computing

سال: 2021

ISSN: ['1568-4946', '1872-9681']

DOI: https://doi.org/10.1016/j.asoc.2021.107376