An intelligent navigation of humanoid NAO in the light of classical approach and computational intelligence

Abstract

Abstract The development of robotics research toward industrialization has created an enhanced demand for modernization of the automation industry. Humanoid robots being advanced than other forms of robots bear a large resemblance to humans and are very much helpful in replacing humans in tedious and repetitive tasks. Therefore, the navigation and path planning of the humanoids bear a large importance in robotics research. The current investigation deals with the path planning of NAO humanoid robots. In the present work, a classical method of regression analysis and an artificial intelligence technique of fuzzy logic are implemented separately for the purpose of obstacle avoidance during the motion of humanoid NAOs toward respective targets. The simulation analysis of the proposed techniques is carried out using V‐REP software. The experiments are performed in laboratory conditions with a proper environment for working of the humanoid NAOs. Finally, a comparison has been made between the simulation and experimental results. The results obtained from the simulation and experimental analyses are in good agreement with each other, which suggest that the proposed methodologies can be used as methods of robust control for the navigation of humanoids.