中文摘要：

为了提高移动机器人在全区域覆盖路径规划中的性能，提出了基于神经元激励神经网络的路径规划算法。介绍了栅格法环境建模原理，使用此方法得到了机器人工作环境的矩阵模型；分析了生物激励神经网络算法，在神经元活性值定义、机器人跳出“死区”两个方面对算法提出了改进，提出了神经元激励神经网络算法。使用此算法对设定的工作环境进行遍历并与生物激励算法进行比较可以看出，在遍历重叠率、路径长度、转弯次数等方面，神经元激励算法都优于生物激励算法，充分说明了改进算法在机器人遍历规划中的优越性。

英文摘要：

To improve performance of complete converage path planning for mobile robot, path planning based on neuronal stimulation neural network is proposed. Grid method used to model working area is introduced, and using this method, matrix model of robot real working area is built. By analyzing the biological stimulation neural network algorithm, this algorithm is improved in two aspects, these are neuronal activity and robot jumping out of dead zone, and the improved algorithm is named by neuronal stimulation neural network. Complete converage path planning for mobile robot in the setting area is executed, the result shows that the new algorithm is superior to the exsiting one in teh overlap rate, path length and turning times. This shows the superiorty of the improved algorithm in complete converage path planning for mobile robot.