Abstract
With the development of the economy and the improvement of people's living standard, social robotics gradually enter into daily lives of individuals. Human-robot interaction is the basic function of social robotics, and how to achieve better experience of human-robot interaction is an important issue in the field of social robotics. Single-person pose estimation is the core technology for human-robot interaction in social robots. Benefiting from the development of deep learning, single-person pose estimation has made great progress. This paper reviews the development of single-person pose estimation from four aspects: data augmentation, the evolution of SPPE model, learning target and post-processing. Besides, we give the commonly used datasets and evaluation metrics. Finally, the problems of SPPE are discussed and the future research trends are given.