Real-Time Self-Localization and Mapping for Autonomous Navigation of Mobile Robots in Unknown Environments

This paper delves into the progressive design and operational capabilities of advanced robotic platforms, highlighting their adaptability, precision, and utility in diverse industrial settings. Anchored by a robust modular design, these platforms integrate sophisticated sensor arrays, including LiDAR for enhanced spatial navigation, and articulated limbs for complex maneuverability, reflecting significant advancements in automation technology. We examine the architectural intricacies and technological integrations that enable these robots to perform a wide range of tasks, from material handling to intricate assembly operations. Through a detailed analysis of system configurations, we assess the implications of such technologies on efficiency and customization in automated processes. Furthermore, the paper discusses the challenges associated with the deployment of advanced robotics, including the complexities of system integration, maintenance, and the steep learning curve for operational proficiency. We also explore future directions in robotic development, emphasizing the potential integration with emerging technologies such as artificial intelligence, the Internet of Things, and augmented reality, which promise to elevate autonomous decision-making and improve human-robot interaction. This comprehensive review aims to provide insights into the current capabilities and future prospects of robotic systems, offering a perspective on how ongoing innovations may reshape industrial practices, enhance operational efficiency, and redefine the landscape of automation technology.

@article{Tolenov2024,
  title     = {Real-Time Self-Localization and Mapping for Autonomous Navigation of Mobile Robots in Unknown Environments},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {10},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Serik Tolenov and Batyrkhan Omarov},
  doi       = {10.14569/IJACSA.2024.0151090},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151090}
}