Abstract: Path planning problem is one of the most important and challenging issues in mobile robot control field. In this paper, the grid method was used to model the robot working environment firstly. Then an improved artificial colony algorithm was put forward for robot path planning. In this algorithm, an adaptive search method was proposed in order to improve the convergence speed of the artificial colony algorithm and the elitist selection strategy was used to avoid the robot path planning falling into a local optimum. Experimental results show the feasibility and effectiveness of the proposed algorithm in path planning for mobile robots.
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Key words: path planning, artificial colony algorithm, adaptive search, elitist selection strategy