AI-Powered Conversational Navigation System for Visually Impaired Using Multi-Modal Real-time Sensing

This comprehensive survey examines the current landscape of artificial intelligence-powered navigation systems designed for visually impaired individuals, with particular emphasis on multi-modal sensing technologies and conversational interfaces. The integration of advanced computer vision, simultaneous localization and mapping (SLAM), and natural language processing has revolutionized assistive mobility devices, offering unprecedented opportunities for enhanced independence and quality of life. This paper presents a systematic analysis of navigation assistance technologies through examination of 60+ peer-reviewed publications from leading IEEE journals, ACM conferences, and prominent research venues. We categorize existing approaches into electronic travel aids, position locator devices, and electronic orientation aids, while analyzing key technological components including object detection algorithms, haptic feedback systems, and voice interface implementations. The survey identifies critical challenges in real-time processing, environmental adaptability, and user acceptance, while proposing a novel AI-powered conversational navigation architecture called ”Robo Guide” that integrates high-resolution sensing, SLAM algorithms, and natural language processing. Our analysis reveals significant research gaps in adaptive learning systems and context-aware assistance, providing directions for future research in developing more intelligent, personalized, and socially acceptable navigation aids. Index Terms—Assistive technology, artificial intelligence, computer vision, navigation systems, visually impaired, SLAM, multimodal sensing, human-robot interaction.