基于认知发育的移动机器人自主导航

Autonomous Navigation for Mobile Robot Based on Cognitive Development

针对未知环境中移动机器人的导航问题,基于生物学的认知和发育机理构建自主导航的认知发育模型。通过自主插入神经元节点,设计结构可动态发育的神经网络,模拟生物的发育特性达到与应用需求相匹配的网络规模。通过热力学过程模拟动物的渐近学习特性,设计认知学习算法,并从理论上证明算法的收敛性。实验结果表明,该模型可使机器人模拟动物从环境中自动获取知识、积累经验,通过认知发育具备自主导航技能。

To solve the navigation problem of mobile robot in unknown environment, based on cognitive development mechanism of biology, a cognitive development model is constructed for mobile robot autonomous navigation. The neural network which can dynamically adjust the structure is designed by autonomous inserting neuron. It is used to imitate the properties of biological development and to obtain the network that can match the application requirements. The asymptotic learning characteristic is imitated through the thermodynamic process and a cognitive learning algorithm is designed, which is proved to be convergence in theory. The results of experiments show that the proposed model can make the robot obtain knowledge automatically and accumulate experience from environment like animal, and learn the skill of autonomous navigation through cognitive development.