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Volume 42 Issue 7
Jul.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(7): 1543-1549.
HE Renke, WEI Ruixuan, ZHANG Qirui, et al. Mimetism electric potential energy motion planning algorithm for aircraft[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(7): 1543-1549. doi: 10.13700/j.bh.1001-5965.2015.0430(in Chinese)
Citation: HE Renke, WEI Ruixuan, ZHANG Qirui, et al. Mimetism electric potential energy motion planning algorithm for aircraft[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(7): 1543-1549. doi: 10.13700/j.bh.1001-5965.2015.0430(in Chinese)
shu

Mimetism electric potential energy motion planning algorithm for aircraft

doi: 10.13700/j.bh.1001-5965.2015.0430

  • Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an 710038, China

  • Received Date: 29 Jun 2015
  • Publish Date: 20 Jul 2016
    Abstract
  • Path planning can ensure that the unmanned aerial vehicle (UAV) flies safely and completes mission successfully. In the complex threat environment and high-dimensional space, traditional path planning methods have some limitations in the aspects of the calculation speed, path security and applicability. In order to solve these problems, the electric potential field distribution characteristics and the law of mechanical work driven by electric field force were studied. The mimetism electric potential energy path planning method was proposed, and the environment model based on the electric potential field distribution and path node probability choice mechanism were established. The relationship between threat intensity and distance was described by using electric potential. Combined with electric potential, the path safety evaluation standard was proposed. On this basis, the potential field based sampling-based random path planning method was proposed. The results show that, compared with traditional methods, the method mentioned above can generate optimal path in consideration of non-holonomic differential constraints, significantly shorten the path length and computational time, and improve the path security, which is of great value for application of path planning.

     

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