【摘要】 针对机器人避障过程中影响因素复杂及难以建立精确模型的问题,采用超声波传感器和定位传感器获取机器人所处环境的输入信息,对其进行模糊处理,并建立三层BP神经网络,进而提出机器人模糊神经网络避障控制算法。仿真结果表明:机器人能从起点安全、无碰撞地避开途中的障碍物,顺利到达终点,实现了安全避障,进而证明该算法能够使机器人在未知环境中准确地避障。更多还原

【Abstract】 Aimed at removing difficulties developing accurate models due to complicated influence factors occurring during the process of obstacle avoidance for robot,this paper describes the adoption of ultrasonic wave sensor and positioning sensor to obtain the input information of environment to which robots are exposed,the fuzzy treatment of the input information,and the development of three-layer BP neural network and proposes the control algorithm of robot fuzzy neural network obstacle avoidance.The simulation shows that this algorithm allows the robot to avoid obstacles accurately in the unknown environment as a result of the robot’s demonstrated ability to avoid the obstacles on the way safely and without collision and reach the destination smoothly before realizing the safety obstacle avoidance.更多还原