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Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

Author

Listed:
  • Yong Ma
  • M. Zamirian
  • Yadong Yang
  • Yanmin Xu
  • Jing Zhang

Abstract

We present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP). With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP). Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.

Suggested Citation

  • Yong Ma & M. Zamirian & Yadong Yang & Yanmin Xu & Jing Zhang, 2013. "Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, February.
    • Handle: RePEc:hin:jnlmpe:613964
    DOI: 10.1155/2013/613964
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    Cited by:

    1. Ahmed, Gamil & Sheltami, Tarek & Mahmoud, Ashraf & Yasar, Ansar, 2020. "IoD swarms collision avoidance via improved particle swarm optimization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 260-278.

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