基于人工免疫网络理论的移动机器人路径规划

针对静态环境下机器人路径规划问题,提出了基于人工免疫网络理论的移动机器人路径规划方法.该方法基于人工免疫网络仲裁机器人的行为,将抗体和抗原类比为机器人的行为和机器人所在的环境,人工免疫网络作为主要的行为仲裁机制,有效地选择和精炼执行任务,并基于Webots实验平台对该方法进行了仿真.实验结果表明,该方法在复杂的环境中具有高度的自制性、适应性、灵活性和有效性.

Mobile-robot path planning based on artificial immune network

The mobile-robot path planning problem in static environment was studied.A approach based on artificial immune network to solve problems was presented and tested in Webots simulator.The method using dynamics of artificial immune network determined the main action of robot.In the experiment,antibody and antigen were simulated as the behavior of robot and environment.The task used an artificial immune network(AIN) to act as an independent behavior arbitration mechanism and hence provided effective and efficient task completion.Simulation experiments with the task phase demonstrated that it was effective for robot navigation in complex scenarios.A Webots simulator was used throughout the experiment.Results showed that high degree of autonomy,adaptability and flexibility could be achieved using this combined method.