Cloud-Integrated Navigation System for Scalable Autonomous Ground Robots
Sharipov U. Kasenov S. Alaran M. Askhatova A. Orynbay Y. Jamwal P.
2024Institute of Electrical and Electronics Engineers Inc.
M2VIP - Proceedings of the International Conference on Mechatronics and Machine Vision in Practice
2024Issue 2024
In the rapidly evolving domain of mobile robots, ensuring both efficient and scalable navigation is of the greatest importance. To effectively address the challenges of real-time navigation this paper presents an innovative approach that includes the synergistic integration of cloud computing and navigation algorithms within a complex framework. The methodology presented in this paper integrates the Dynamic Window Approach (DWA) for real-time obstacle avoidance and the A* algorithm for global planning in indoor environments. The proposed system in conjunction with cloud computing is capable of processing and analyzing vast amounts of environmental data, providing robust and scalable navigation capabilities. Our solution ensures that autonomous delivery robots can navigate complex, dynamic, and socially dense urban environments with unprecedented efficiency and safety.
Autonomous Ground Vehicles , Obstacle Avoidance , Path Planning , Simultaneous Localization and Mapping
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Nazarbayev University, Astana, Kazakhstan
Nazarbayev University, Astana, Kazakhstan
Nazarbayev University, Astana, Kazakhstan
Nazarbayev University
Nazarbayev University
Nazarbayev University
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026