Performance Evaluation of Humanoid Robot Imitation Skills Using the MOORA Method

Abstract

One of the key challenges in developing humanoid robots is enabling them to imitate human actions and behaviors accurately. This abstract explores the concept of humanoid robot imitation, highlighting its significance, challenges, and potential applications. Imitation is a fundamental aspect of human learning and social interaction. Humans learn by observing and imitating the actions of others, which is essential for acquiring new skills and adapting to various situations. This natural ability to imitate is a crucial factor in the development of humanoid robots, as it allows them to integrate seamlessly into human environments and assist with tasks that require human-like movements and behaviors. Understanding imitation in robots can lead to the development of more capable and versatile machines that can perform tasks in human environments. As robots become more integrated into human workplaces and daily life, it's essential for them to interact seamlessly with humans. Research on imitation helps improve the ability of robots to collaborate effectively with humans, enhancing productivity and safety in shared spaces. Humanoid robots have the potential to play significant roles in social settings, like companions for the elderly, educational assistants for children, or customer service agents. Understanding imitation in robots can enhance their ability to engage socially and build trust with humans. Versatile with unique alternatives a new method for optimization is proposed MOORA. This method is objective denotes the matrix of responses of the alternatives, however, proposing better policies, which rates are used. Well established. Multi-objective another method for optimization is used for comparison, reference point method. Then, various competitions this proved to be the best choice among the methods. From the result Alter 3 is in got first rank where as Ameca is in lowest rank.