Mobile robot path planning is an important part of the mobile robot field. The swarm intelligence optimisation algorithm has certain advantages in solving such multi-objective optimisation problems, so this Letter pro...
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Mobile robot path planning is an important part of the mobile robot field. The swarm intelligence optimisation algorithm has certain advantages in solving such multi-objective optimisation problems, so this Letter proposes to apply the pigeon-inspired optimisation (pio) algorithm to the path planning problem. However, the traditional pioalgorithm is suffering from the problems of easy to get into local optimisation, low stability and premature convergence. To overcome its shortcomings, this Letter proposes a logistic beetle algorithmsearch-pio (LBAS-pio) algorithm. In the optimisation process of the LBAS-pioalgorithm, the pioalgorithm is initialised by the logistic mapping, making the search space more extensive. Learning from the idea of the beetle algorithmsearch, each pigeon has its own judgment of the environment and the number of iterations and search time are reduced. Further, the path evaluation function of the algorithm and the execution order of the operators are optimised to make the algorithm smoother and easier to find the global optimal solution. Simulation and experimental results illustrated the superiority of the LBAS-pioalgorithm and the LBAS-pioalgorithm better meets the needs of mobile robots for the optimal path planning.
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