通过对蚁群算法原理的分析及机器人路径规划的研究,在MMAS的基础上,引入节点活跃度的蚁群算法,对基于栅格法的机器人路径搜索收敛性进行了数值模拟研究,结果表明,在改进的蚁群算法控制下,收敛速度较快且全局稳定性较高。完成了机器人分级控制系统的硬件设计与软件设计,通过实验测试,验证了控制系统在复杂环境下的高效寻迹能力。 Based on the analysis of the principle of ant colony algorithm and robot path planning, an ant colony algorithm based on MMAS is introduced to study the convergence of robotic path search based on grid method. The results show that, Under the control of the improved ant colony algorithm, the convergence speed is faster and the global stability is higher. The hardware design and software design of the robot grading control system are completed. The experimental results show that the control system can efficiently traverse the complex environment.