机器人动态神经网络导航算法的研究和实现  

Research and realization of dynamic neural network navigation algorithm for mobile robot

作　　者：乔俊飞[1] 樊瑞元[1] 韩红桂[1] 阮晓钢[1] 

机构地区：[1]北京工业大学电子信息与控制工程学院,北京100124

出　　处：《控制理论与应用》2010年第1期111-115,共5页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60674066;60873043);国家"863"计划资助项目(2007AA04Z160);北京市自然科学基金资助项目(4092010);教育部博士点基金资助项目(200800050004)

摘　　要：针对Pioneer3-DX移动机器人,提出了基于强化学习的自主导航策略,完成了基于动态神经网络的移动机器人导航算法设计.动态神经网络可以根据机器人环境状态的复杂程度自动地调整其结构,实时地实现机器人的状态与其导航动作之间的映射关系,有效地解决了强化学习中状态变量表的维数爆炸问题.通过对Pioneer3-DX移动机器人导航进行仿真和实物实验,证明该方法的有效性,且导航效果明显优于人工势场法.For the navigation of Pioneer3-DX mobile robot in unknown environment, we propose a self-navigation strategy with learning reinforcement, and develop the navigation algorithm based on the dynamical neural network. The dynamically self-organizing neural network can automatically adjust its structure according to the complexity of the working environments of the mobile robot to realize the mapping between environmental states and robot actions, effectively avoiding the dimension explosion in learning reinforcement. Simulations and real robot navigation experiments are carried out; results show that the proposed method is effective in applications. It gives a better navigation performance than that of the artificial potential-field method.

关 键 词：移动机器人 导航 动态神经网络 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]