Research on Key Technologies in Autonomous Navigation of Robotic Vehicles

DOI

10.2991/978-94-6463-823-3_38How to use a DOI?

Keywords

Autonomous Navigation; Environmental Perception; SLAM; Path Planning; Internet of Vehicles

Abstract

Autonomous navigation technology for robotic vehicles is an important research direction in the fields of intelligent transportation, autonomous driving and unmanned systems. This technology enables vehicles to perceive the surrounding environment in real time, plan reasonable paths, and drive safely and efficiently in unknown or complex environments. In recent years, with the rapid development of technologies such as computer vision, artificial intelligence, and wireless communication, robotic vehicles have achieved enhanced navigation capabilities, including better perception and decision-making. However, there are still many challenges in terms of dynamic environmental adaptability, real-time decision-making, safety, and robustness. This paper systematically examines five key technologies in robotic vehicle navigation: environmental perception and sensor fusion, simultaneous localization and mapping (SLAM), path planning, motion control, and vehicle networking. Each technology addresses specific aspects of autonomous navigation. First, environmental perception technology achieves accurate perception of complex road environments through multi-sensor fusion and improves the reliability of the navigation system. Second, SLAM technology is used for positioning and mapping robotic vehicles in unknown environments and is the core technology for achieving autonomous navigation. Path planning methods ensure that the vehicle can determine optimal routes for obstacle avoidance and safe passage. In addition, motion control technology determines whether robotic vehicles can execute the planned path smoothly and accurately. Finally, the Internet of Vehicles technology supports improving traffic coordination efficiency and optimizing driving experience.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Siyu Liu
PY  - 2025
DA  - 2025/08/31
TI  - Research on Key Technologies in Autonomous Navigation of Robotic Vehicles
BT  - Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)
PB  - Atlantis Press
SP  - 387
EP  - 395
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-823-3_38
DO  - 10.2991/978-94-6463-823-3_38
ID  - Liu2025
ER  -