中文摘要：

机器人路径规划技术是机器人研究的一个重要领域。针对未知的全局环境,使机器路径最优化,利用机器人传感器网络建立可视区域,将整体任务分解为环境信息已知的一系列子任务,利用神经网络高速并行计算的优点,建立神经网络罚函数,提出一种实时性较高的变参数方法离散化求取罚函数的负梯度方向,控制机器人快速高效地完成子任务,从而驱使机器人到达目标点并进行仿真。仿真结果证明了复杂环境静态和动态目标指引下方法的有效性和实用性,特别适用于实时性要求高的场合。

英文摘要：

Path Planning technology for mobile robots is an important subject of robotics studies.For unknown global environment,in this paper,the whole task is decomposed to a series of sub - tasks with known and simple environment through the robot＇s sensor network.Then a discrete neural network penalty function is constructed by using the parallel computing predominance of neutral network,and then a variable - parameter method is introduced to obtain the negative gradient direction of the penalty function and solve the sub-tasks fast and efficiently.So,the robot can be driven to the goal.This strategy simplifies the path - planning algorithm in complex environment,and improves the control effects.Especially for a real - time situation,it has distinct advantages.