具有负反馈机制的改进的蚁群算法在机器人路径规划中的应用

Robot Path Planning by Improved Ant Colony Algorithm and Negative Feedback Mechanism

蚁群优化算法是一种可以有效解决机器人路径规划问题的方法,为加快收敛速度,部分学者从正反馈方面做出一些改进,但这些改进方式在复杂环境中依旧容易陷入局部最优解。为解决上述问题,运用栅格法对场景实施建模,并通过蚁群算法找出简单及其复杂条件下的最优路径,之后,设计具有负反馈机制的改进蚁群算法,用于解决机器人规划方面的问题。实验表明,该算法能够通过负反馈有效改善解多样性问题,有利于迅速获取最优解。

Ant colony optimization is a useful method that can solve the problem of robot path planning. In order to accelerate convergence rate, scholars have made some improvements from positive feedback aspect, while these methods for improvement are easily to fall into locally optimal solution in complex environment. Aiming at solving the above problem, the paper uses grid method to make a model of implementation scenario, finds optimal path under simpleness and complex conditions by ant colony algorithm. At the same time, it makes a design of improved ant colony algorithm that has negative feedback mechanism, to solve the problem of robot path planning. By the negative feedback, the arithmetic can solve diversity problem, it is beneficial to obtain optimal solution.