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Research on path planning and TSP based on genetic algorithm and Hopfield neural network

Lingxiao Yang, Huanzhang Zhou

Year
2011
Citations
6

Abstract

In the mobile robot technology, path planning is an important question. In this paper it gets the model information of global static environment by raster method, and by the genetic algorithm it can obtain the population diversity of the optimal planning path avoiding successfully obstacles and going through the designated points, then Hopfield neural network is used to solve the traveling salesman problem(TSP) and optimal round-trip problem of passing through the designed points, the proposed method is feasible and effective, the simulation results in the Matlab show better optimization effect.

Keywords

Travelling salesman problemMotion planningGenetic algorithmComputer scienceArtificial neural networkPath (computing)Mathematical optimizationMATLABMobile robotPopulation

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