| Issue |
ITM Web Conf.
Volume 80, 2025
2025 2nd International Conference on Advanced Computer Applications and Artificial Intelligence (ACAAI 2025)
|
|
|---|---|---|
| Article Number | 03009 | |
| Number of page(s) | 7 | |
| Section | Robotics, Autonomous Systems & Sensor Fusion | |
| DOI | https://doi.org/10.1051/itmconf/20258003009 | |
| Published online | 16 December 2025 | |
Application of Route Planning and Obstacle Avoidance System
Affiliated High School of South China Normal University International Department, Guangzhou, 510000, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Recently, research on route planning technologies and obstacle avoidance has gained increasing attention with the rapid development of artificial intelligence. These fundamental technologies are applied in operating systems to support robotic navigation and transfer tasks. Nonetheless, challenges such as lag and uncertainty in predictions remain unsolved, limiting the efficiency and stability of practical applications. To address these issues, scientists continue to explore optimization methods. This paper will introduce such technologies by explaining their definitions, working principles, and coding implementations. Furthermore, a design scheme will be presented as a practical reference, illustrating how these concepts can be applied dynamically. Through this discussion, the paper seeks to encourage further exploration and inspire potential solutions or revisions to overcome existing technical barriers. Moreover, the paper shares the basic theory for helping advanced learning of the technologies, not for the comprehensive application of the operating system, so any sharing of the program is to help appreciate the application of technologies.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

