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Level Set Based Path Planning Using a Novel Path Optimization Algorithm for Robots

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Abstract

In order to decrease the path length and control the minimum distance between the path and the obstacles when the level set based path planning algorithm is adopted, a new path optimization algorithm named elastic particle is proposed in this paper. Firstly, the iteration expression of optimization algorithm is deduced by active contour theory. Secondly, to ensure the convergence of algorithm, the relation among each item in the algorithm expression is analyzed and its convergence condition is determined. At last, level set algorithm is improved so that the smoothness of the initial path and the convergence speed of the algorithm are improved. In addition, a method named the nearest boundary distance is put forward to accelerate the operation speed of the algorithm. What’s more, memory pool and binary sort tree are adopted in the code to further reduce the running time of this algorithm. The optimal values of the algorithm parameters are analyzed via the simulation experiment,and its result demonstrates that the new algorithm has greatly optimized the path of algorithm-level set and guaranteed fast running speed and high reliability.

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Correspondence to Wei Zhang or Sungki Lyu.

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Zhang, XG., Zhang, W., Li, H. et al. Level Set Based Path Planning Using a Novel Path Optimization Algorithm for Robots. Int. J. Precis. Eng. Manuf. 19, 1331–1338 (2018). https://doi.org/10.1007/s12541-018-0157-1

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  • DOI: https://doi.org/10.1007/s12541-018-0157-1

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