关键词: 移动机器人, 路径规划, 蚁群算法, 信息素差异化

Abstract: As for original ant colony algorithm using in mobile robot path planning, there are problems such as the convergence speed and searching ability existing unbalance, falling into local optimum easily and so on. In this paper, an adaptive improved ant colony algorithm is proposed. Firstly, in order to improve convergence speed of the algorithm, in the grid environment the initial pheromone is differentiate distributed according to the characteristics of the optimal path and the basic parameters of the actual environment. Secondly, in order to raise the efficiency of ants search, the turn-angle heuristic information is introduced into the state transition probability and the path heuristic information is improved. Thirdly, it reformulates the strategy of pheromone renewal, sets the iteration threshold, and the pheromone volatilization coefficients and pheromone concentration are adjusted, so that at the later stage of iteration, the algorithm still has a strong ability to search for the optimal solution. Finally, the piecewise third-order Besizer curve is used to smooth the optimal path to meet the actual motion requirements of the robot. The feasibility, effectiveness and superiority of the improved algorithm are verified by comparing with other algorithms.

Key words: mobile robot, path planning, ant colony algorithm, pheromone differentiation