基于Boltzmann机神经网络认知机制的机器人趋光控制

Robot phototaxis control based on Boltzmann machine neural network cognitive mechanism

针对移动机器人未知环境下的趋光控制问题,模拟人或动物"感知-行动"认知机制,对具有趋光特性的移动机器人进行设计,提出一种基于Boltzmann机神经网络的趋光控制方法.该方法首先应用知识集对机器人趋光控制器的Boltzmann机神经网络进行趋光训练;然后应用Boltzmann机神经网络的运行机制实现趋光控制.仿真实验表明,该方法能够提高机器人学习的控制精度.

For mobile robot phototaxis control problems, the human or animal“perception-action”cognitive mechanism is simulated. The structure of mobile robot is designed and the method of phototaxis control is proposed based on the Boltzmann machine neural network. The Boltzmann machine neural network is trained by the knowledge set. The phototaxis control method is implemented by using the Boltzmann machine neural network operation mechanism. Simulation results show that the proposed method can improve the control accuracy and the success rate of robot learning.