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A new approach to smooth global path planning of mobile robots with kinematic constraints

  • Baoye Song
  • Zidong WangEmail author
  • Lei Zou
  • Lin Xu
  • Fuad E. Alsaadi
Original Article

Abstract

This paper is concerned with the planning problem of smooth global path for mobile robots with kinematic constraints. A new approach is proposed that is based on a modified particle swarm optimization (MPSO) combined with the η3-splines. Some preliminaries on η3-splines are first introduced to interpolate an arbitrary sequence of points with assigned kinematic parameters associated with the motion and control of mobile robots. Then, the MPSO algorithm with adaptive random fluctuations (ARFs) is proposed to deal with the frequently encountered local convergence issue in the planning of the global smooth path. In the MPSO algorithm, the evolutionary state is classified averagely at each iteration according to the evaluated evolutionary factor, where the velocity updating dynamics switches among various modes according to the evolutionary state and the ARFs are enforced on the global/local best particles in each mode of the current iteration. The proposed MPSO is verified to outperform five other well-known PSO algorithms via comprehensive simulation experiments on a collection of benchmark functions. Finally, the new approach by combining the MPSO algorithm with the η3-splines is exploited to handle a double-layer smooth global path planning problem with several kinematic constraints.

Keywords

Smooth path planning Mobile robots Modified particle swarm optimization Adaptive random fluctuations η3-splines 

Notes

Acknowledgements

This work was supported in part by the Research Fund for the Taishan Scholar Project of Shandong Province of China and the Higher Educational Science and Technology Program of Shandong Province of China under Grant J14LN34.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.College of Electrical Engineering and AutomationShandong University of Science and TechnologyQingdaoChina
  2. 2.Department of Computer ScienceBrunel University LondonUxbridgeUK
  3. 3.Department of Electrical and Computer Engineering, Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia

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