In this work we report two successful cases of developing neural networks of spiking neurons for controlling mobile robots. In the first case we use a toy robot, a crocodile, driven by a neural network in-silico. We show that this so-called neuroanimat is capable of detecting internal events of synchronization of network responses to stimuli. In the second example we employ a spiking neural network for building a human-robot interface. Using a bracelet with eight electromyographic sensors we have shown that the interface can faithfully detect myographic signals, classify them according to hand gestures, and send the corresponding commands to the robot. Although the two applications belong to different areas of Neuroscience, they are based on a common approach of neural computations. We note that in both cases besides neural networks there are no additional external algorithms for the decision-making.