Path Planning for UAV Based on Improved PRM

Weimin Li, Lei Wang (), Awei Zou, Jingcao Cai (), Huijuan He and Tielong Tan
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Weimin Li: School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Lei Wang: School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Awei Zou: School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Jingcao Cai: School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Huijuan He: School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Tielong Tan: Wuhu Kepu Intelligent Equipment Co., Ltd., Wuhu 241000, China

Energies, 2022, vol. 15, issue 19, 1-16

Abstract: In this paper, an improved probabilistic roadmap (IPRM) algorithm is proposed to solve the energy consumption problem of multi-unmanned aerial vehicle (UAV) path planning with an angle. Firstly, in order to simulate the real terrain environment, a mathematical model was established; secondly, an energy consumption model was established; then, the sampling space of the probabilistic roadmap (PRM) algorithm was optimized to make the obtained path more explicit and improve the utilization rate in space and time; then, the sampling third-order B-spline curve method was used to curve the rotation angle to make the path smoother and the distance shorter. Finally, the results of the improved genetic algorithm (IGA), PRM algorithm and IPRM algorithm were compared through a simulation. The data analysis shows that the IGA has significant advantages over other algorithms in some aspects, and can be well applied to the path planning of UAVs.

Keywords: UAV; improved PRM algorithm; energy consumption; path planning; B-spline curve (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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