NAO version 5 is a 58 cm humanoid robot with a weight of 5.2 kilogram. It has 25 degrees of freedom with 4 microphones and 2 speakers. It consists of 1 GB of RAM, 2 GB Flash memory and 8 GB Micro SDHC. It supports C , python and Java. There have been numerous journals which researched on NAO robots playing certain games. [Motor Actions Prediction and Control for the NAO Robot Playing Hand Clapping Games] was able to make the robot play hand clapping games. This paper was able to adapt to random hand motions in a timely fashion without any pre-planned information. Additionally, it used Probability Movement Primitives (ProMPs) or human motion prediction and improved the accuracy through a motion recognition process with Heininger distance. To encode the possibility region of future human motions, an implicit Dynamic Movement Primitives (DMPs) was generated capturing different dynamics on one short for robot motion model. At last Model Predictive Controller (MPC) was applied to track K-step for- ward human motions to achieve time synchronization and joint goals. [Design and implementation of kinematics model and trajectory planning for NAO humanoid robot in a tic-tac-toe board game] was successful in making the robot play tic-tac-toe games by presenting kinematic models for the robot#8217;s upper body. Finally, [Complete Analytical Forward and Inverse Kinematics for the NAO Humanoid Robot] studied the problems of forward and inverse kinematics for the Aldebaran NAO humanoid robot and presented a complete, exact, analytical solution to both problems, including a software library implementation for real-time on-board execution.