Towards Biologically Inspired Neural Controllers for Intelligent Robots : A BMI Approach

最近关于脑机接口(BMI)的工作在开发旨在恢复瘫痪患者运动功能的假体设备方面取得了有希望的结果。这项工作的目标是创造一种部分机械、部分生物的机器人，它根据大鼠脑细胞的神经活动进行操作。在我们的方法中，首先，老鼠通过按下左右杠杆来学习移动机器人，以便获得食物。然后，我们利用多电极记录的数据来训练人工神经控制器，然后将其用于基于大鼠大脑活动的机器人运动控制。结果表明，人工神经网络控制真实机器人具有良好的性能。

Recent works on Brain Machine Interface(BMI) has given promising results for developing prosthetic devices aimed at restoring motor functions in paralyzed patients. The goal of this work is to create a part mechanical, part biological robot that operates on the basis of the neural activity of rat brain cells. In our method, first the rat learns to move the robot by pressing the right and left lever in order to get food. Then, we utilize the data of multi-electrode recordings to train artificial neural controllers, which are later employed to control the robot motion based on the brain activity of rats. The results show a good performance of artificial neural network controlling the real robot.