基于混沌蚁群算法的机器人路径规划

Ant Algorithm for Navigation of Robot Movement in Complex Environment

研究了全局静态复杂环境的机器人导航问题;针对传统蚁群极易陷入局部最优解,引入混沌理论改善个体质量,利用混沌扰动避免在搜索过程中陷入局部极值;构建了一个新的机器人路径规划算法的数学模型,在组织变量的影响下,蚂蚁由最初的混沌行为逐渐过渡为群体智能行为,最终完成机器人全局最优路径的搜索;仿真结果表明,即使在障碍物非常复杂的环境中,该模型也能找出一条全局最优或近似最优的路径,且能安全避障,仿真效果理想。

The navigation problem of robot movement in a complex environment is studied in the paper.Because the traditional ant colony algorithm is easy to drop into local optimum as searching the shortest path,a chaotic theory is embedded into the modified Version,which is used to improve individual quality.Chaos perturbation should be utilized to avoid the search being trapped in local optimum.A new Robot path planning is modeled,the ants change chaotic behavior to swarm intelligence by the effect of organizational variables.The simulation results indicate that the optimal path,which the robot moves on,can lead the robot to reach the end safely even in complicated environment.The effect is very satisfactory.