Abstract: One of the goals pursued by robotics research is to operate dexterously like humans in complex and changeable unstructured environments. The spiking neural network (SNN) inspired by the working mode of the biological brain is the main working paradigm in the field of brain-inspired intelligence. It has good biological rationality and has attracted increasing attention in the field of robot intelligent control. We provide a review of research related to SNN-based robot brain-inspired intelligent control, hoping to bring inspiration to research in the field of robots and brain-inspired intelligence. Firstly, we introduce SNN-related knowledge such as the development history of SNN, neuron models, encoding methods, synaptic plasticity and network structure. Secondly, by drawing on the human motion feedback control mechanism, we give a framework for robot brain-inspired intelligent control based on SNN. Thirdly, we introduce the research progress of robot brain-inspired intelligent control strategies from three aspects: motion control, compliance control, and collaborative control. Finally, the SNN-based robot brain-inspired intelligent control technology is summarized and prospected.