Research of improved ant colony optimization in mobile robot path planning

doi:10.16731/j.cnki.1671-3133.2017.05.009

Abstract

Abstract: Aiming at solving defects such as slow convergence speed,low efficiency,frequent local optimum,and even the emergence of deadlock in the path planning of introducing the traditional ant colony algorithm into mobile robots,an advanced ant colony algorithm is proposed,which establishes the working environment of the robot by grid method,improves updating mode of information pheromone,sets the pheromone concentration threshold,introduces treatment strategy of deadlock,and thus improves the state transition probability and increases the diversity of solutions.Simulation tests for mobile robot path planning are carried out in the grid environment.The results of simulation tests show that the improved ant colony algorithm can narrow the search scope of the optimal path and reduce the number of iterations,improve the search efficiency of the optimal solution,and can obtain the global optimum collision-free path.

Key words: path planning, mobile robot, ant colony algorithm, grids, optimal path

CLC Number:

TP242

Zuo Dali, Nie Qingbin, Zhang Liping, Ding Dukun. Research of improved ant colony optimization in mobile robot path planning[J]. Modern Manufacturing Engineering, 2017, 440(5): 44-48.

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