Artificial Intelligence-Driven Innovations in SLAM for Robotics and Autonomous Navigation
Zheming Wang, Xinguang Zhang · 2025
SLAM is foundational to robots and autonomous navigation as it allows machines to navigate and create a map of space at once. This review article discusses incorporating artificial intelligence (AI) into the SLAM process to improve the mapped environment perception for improved navigation, reducing the perceived herald weaknesses of conventional methods. The topics covered are the difficulties in incorporating AI into existing SLAM systems, the dilemma of privacy concerns while using data sources, and the deficit of skilled employees in the workforce. Solutions being suggested are initiating research works that feature both conventional approaches and AI methodologies, encouraging academic-industry partnerships, and investing in education. The practicality of these solutions is backed by exemplars that show high levels of enhanced performance in some applications; the path is cleared for smarter, self-controlled systems.