Systematic Study of the Research Progress in Intelligent Logistics Robot
- DOI
- 10.2991/978-94-6463-821-9_33How to use a DOI?
- Keywords
- Automated Guided Vehicle; Path Planning; Control Algorithm; PID Control
- Abstract
This paper summarizes and discusses the electronic control technology and mechanical structure technology involved in the development and design of AGV (Automated Guided Vehicle), a branch of the rapidly developing robotic technology, and prospects its future development based on the progress and trends of existing related technologies. Firstly, it provides a brief introduction to AGVs applied in different scenarios and analyzes the unique mechanical structures for different functions. Then, it proposes three popular guidance methods and analyzes their advantages and disadvantages with examples. As one of the key technologies of intelligent warehousing, AGV path planning has always been a research hotspot at home and abroad. The tracking algorithm, as a key function of path planning, still mostly adopts the closed-loop control strategy based on error feedback to eliminate system tracking errors. This paper introduces fuzzy control and proposes an improved fuzzy PID control, and finally introduces a multi-sensor fusion algorithm, the extended Kalman filtering method.
- 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.
Cite this article
TY - CONF AU - Zihan Ye PY - 2025 DA - 2025/08/31 TI - Systematic Study of the Research Progress in Intelligent Logistics Robot BT - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025) PB - Atlantis Press SP - 303 EP - 314 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-821-9_33 DO - 10.2991/978-94-6463-821-9_33 ID - Ye2025 ER -