Simultaneous Localization and Mapping (SLAM) with 3D Vision for Robotics

Abstract

Simultaneous Localization and Mapping (SLAM) is a fundamental challenge in robotics, essential for autonomous navigation in unknown environments. With the advent of 3D vision technology, SLAM has seen significant advancements, enabling robots to understand and navigate complex environments with higher accuracy and reliability. This paper explores the integration of 3D vision with SLAM, discussing the underlying principles, algorithms, and applications. It also highlights current trends and future directions in the field, emphasizing the impact of machine learning and artificial intelligence on enhancing SLAM capabilities.