Navigation in autonomous mobile robots

This paper explores the design and development of Autonomous Mobile Robots (AMRs) using the Robot Operating System (ROS) for intelligent navigation. AMRs equipped with ROS can perceive their environment, planning optimal paths, and making real-time decisions, making them suitable for a wide range of industrial and service-based applications. The integration of technologies such as Simultaneous Localization and Mapping (SLAM), sensor fusion, and dynamic obstacle avoidance enables these robots to operate reliably in both known and unknown environments. The report highlights how core ROS components like navigation stacks, cost maps, and transform libraries contribute to flexible and scalable robot behavior. It also examines the challenges involved in localization, path planning, and hardware software integration, offering insights into emerging solutions such as AI-enhanced navigation, edge computing, and ROS2 enhancements. By focusing on real-world applicability and innovation, this report shows the growing potential of ROS-powered AMRs in autonomous navigation.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.17222740
Primary Topic
China's Socioeconomic Reforms and Governance
Type
article
Field-Weighted Citation Impact
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article

Navigation in autonomous mobile robots

Zenodo (CERN European Organization for Nuclear Research)
China's Socioeconomic Reforms and Governance
article

Navigation in autonomous mobile robots

article en

Abstract

This paper explores the design and development of Autonomous Mobile Robots (AMRs) using the Robot Operating System (ROS) for intelligent navigation. AMRs equipped with ROS can perceive their environment, planning optimal paths, and making real-time decisions, making them suitable for a wide range of industrial and service-based applications. The integration of technologies such as Simultaneous Localization and Mapping (SLAM), sensor fusion, and dynamic obstacle avoidance enables these robots to operate reliably in both known and unknown environments. The report highlights how core ROS components like navigation stacks, cost maps, and transform libraries contribute to flexible and scalable robot behavior. It also examines the challenges involved in localization, path planning, and hardware software integration, offering insights into emerging solutions such as AI-enhanced navigation, edge computing, and ROS2 enhancements. By focusing on real-world applicability and innovation, this report shows the growing potential of ROS-powered AMRs in autonomous navigation.

Zenodo (CERN European Organization for Nuclear Research)
Symbiosis International University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
China's Socioeconomic Reforms and Governance
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Navigation in autonomous mobile robots · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS