DEVELOPMENT OF AI-BASED ROBOT NAVIGATION SYSTEMS
Keywords:
robot navigation, artificial intelligence, deep learning, SLAM, path planning, sensor fusion, reinforcement learning, autonomous systems.Abstract
This paper presents a comprehensive study on the development and implementation of artificial intelligence-based navigation systems for autonomous robots. We examine the integration of machine learning algorithms, deep neural networks, simultaneous localization and mapping (SLAM), reinforcement learning, and sensor fusion techniques to enable robust, real-time robot navigation in both structured and unstructured environments. Through experimental evaluation on standard benchmark datasets, we demonstrate that AI-powered navigation significantly outperforms traditional rule-based approaches, achieving up to 97.8% obstacle detection accuracy, 78.6% reduction in localization error, and 51.4% improvement in navigation speed. Our findings underscore the transformative role of AI in advancing autonomous robotics and highlight critical research directions for future development.
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