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ROS-Based Navigation and Obstacle Avoidance: A Study of Architectures, Methods, and Trends
Zhe Wei1, Sen Wang1, Kangyelin Chen2
1School of Computer Science, Civil Aviation Flight University of China, Guanghan 618307, China.
Sensors (Basel, Switzerland)
|July 30, 2025
Summary
This study examines the Robot Operating System (ROS) navigation stack for mobile robots. It analyzes obstacle avoidance, compares local planners like DWA and TEB, and reviews challenges and trends for safer autonomous navigation.
Area of Science:
- Robotics
- Artificial Intelligence
- Computer Science
Background:
- The Robot Operating System (ROS) has significantly advanced mobile robot autonomous navigation.
- ROS integrates key components like SLAM, localization, global path planning, and obstacle avoidance.
- Safe navigation in dynamic environments presents challenges due to real-time perception and sensor fusion.
Purpose of the Study:
- To systematically examine the ROS-based navigation stack and obstacle-avoidance mechanisms.
- To analyze the architecture and implementation of core ROS navigation modules.
- To compare local planners (DWA, TEB) and review emerging trends in autonomous navigation.
Main Methods:
- Systematic examination of ROS navigation stack architecture.
- Analysis of core module implementation principles.
- Comparative study of Dynamic Window Approach (DWA) and Timed Elastic Band (TEB) local planners.
Main Results:
- Detailed analysis of ROS navigation stack components and their integration.
- Comparison of DWA and TEB suitability for different applications.
- Identification of key challenges and recent advancements in ROS-based navigation.
Conclusions:
- The study provides a deeper theoretical understanding of robotic navigation using ROS.
- Offers practical guidance for designing and developing robust autonomous systems.
- Highlights emerging trends like deep learning integration and multi-robot coordination.
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