Design of Intelligent Obstacle Avoidance Car Based on STM32
- DOI
- 10.2991/978-94-6463-518-8_21How to use a DOI?
- Keywords
- STM32; Obstacle avoidance; Intelligent car
- Abstract
With the rapid development of science and technology and the continuous improvement of people’s demand for automation and intelligent life, intelligent mobile robot technology has become a key field of scientific and technological research, development and application. In the development of intelligent mobile robot technology, intelligent car design has become a popular branch. This paper designs an intelligent obstacle avoidance car system based on STM32 microprocessor. This design uses 32-bit high frequency processor STM32F103C8T6 as the core processor of intelligent car system. It uses PWM to control the motor. The servo module, ultrasonic module, infrared tracking module and Bluetooth module are used to realize the following function, obstacle avoidance function, infrared tracking function and Bluetooth control function of intelligent obstacle avoidance vehicle. This design can be applied to the frontier design of intelligent field. It is hoped that it can provide useful reference and inspiration for researchers in related fields.
- Copyright
- © 2024 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 Bi PY - 2024 DA - 2024/09/28 TI - Design of Intelligent Obstacle Avoidance Car Based on STM32 BT - Proceedings of the 2024 International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2024) PB - Atlantis Press SP - 197 EP - 209 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-518-8_21 DO - 10.2991/978-94-6463-518-8_21 ID - Bi2024 ER -