Robots designed for human interaction require advanced Natural Language Processing (NLP) capabilities to understand and respond to user queries effectively. This is particularly crucial in multilingual environments where user-friendly communication ensures broader accessibility. Leveraging advancements in NLP, this project proposes the development of a conversational system for robots using a Transformer-based model, such as BERT (Bidirectional Encoder Representations from Transformers) or GPT, optimized for multilingual interaction. This system aims to enable seamless, context-aware communication across multiple languages. The development of automated systems future to improve user experiences across a range of fields has been speeded up by the quick development of robotics and artificial intelligence (AI). The architecture, features, and practical uses of AI-powered receiving robots are the main topics of this review article, which discovers their development and deployment. These robots can communicate with people, schedule activities, and deliver information since they are prepared with machine learning algorithms, facial acknowledgment software, and natural language processing (NLP). The conversation starts with a thorough rundown of the fundamental parts of these robots, such as communication procedures, software structures, and hardware settings. It highlights how AI methods like deep learning for picture and speech recognition are integrated, which adds to their inefficiency and versatility in a variety of settings, including hotels, healthcare facilities, and business offices. The study also aspects at the difficulties of creating and applying AI reception robots, including data protection, ethical issues, and making sure the robots are resilient in changing environs. Performance principles such as response accuracy, user happiness, and system dependability are assessed through the analysis of real-world case studies. In order to better meet user requirement, future prospects are finally covered, with a focus on the possibility of improved autonomy, multilingualism, and emotive intelligence. The innovative potential of AI-powered receiving robots to redefine customer service and operational efficiency is highlighted in this analysis.