STM32-based floor sweeping robot

This dissertation presents the design and implementation of an intelligent cleaning robot based on the STM32F103 microcontroller, integrating autonomous navigation, environmental sensing, and IoT connectivity. The system employs dual STM32F103 controllers to generate PWM signals for motion con...

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Main Author: Li, Jianming
Other Authors: Wang Qijie
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2025
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Online Access:https://hdl.handle.net/10356/182894
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1828942025-03-07T15:51:05Z STM32-based floor sweeping robot Li, Jianming Wang Qijie School of Electrical and Electronic Engineering qjwang@ntu.edu.sg Engineering This dissertation presents the design and implementation of an intelligent cleaning robot based on the STM32F103 microcontroller, integrating autonomous navigation, environmental sensing, and IoT connectivity. The system employs dual STM32F103 controllers to generate PWM signals for motion control: one governs four TT motors with PID-based speed regulation and quadrature encoder feedback, while the other drives an SG90 servo for brush head adjustment. Obstacle avoidance is achieved through real-time distance monitoring using HC-SR04 ultrasonic sensors, ensuring collision-free navigation. A modular communication architecture is developed, utilizing ESP01S for Wi-Fi connectivity and USART interfaces to interconnect three STM32 units, enabling remote control via a custom Android app developed with AppInventor. Additional functionalities include environmental monitoring via timer based input capture for temperature/humidity sensing and an I²C-driven OLED interface for real-time parameter visualization. Experimental results validate the system’s robustness in adaptive speed control, obstacle detection accuracy (<3 cm error), and low-latency wireless communication (<150 ms). The work demonstrates a cost-effective, scalable framework for smart home devices, balancing hardware efficiency with software flexibility. Future extensions could incorporate machine learning for path optimization or multi-robot coordination. Master's degree 2025-03-06T00:38:15Z 2025-03-06T00:38:15Z 2025 Thesis-Master by Coursework Li, J. (2025). STM32-based floor sweeping robot. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/182894 https://hdl.handle.net/10356/182894 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
spellingShingle Engineering
Li, Jianming
STM32-based floor sweeping robot
description This dissertation presents the design and implementation of an intelligent cleaning robot based on the STM32F103 microcontroller, integrating autonomous navigation, environmental sensing, and IoT connectivity. The system employs dual STM32F103 controllers to generate PWM signals for motion control: one governs four TT motors with PID-based speed regulation and quadrature encoder feedback, while the other drives an SG90 servo for brush head adjustment. Obstacle avoidance is achieved through real-time distance monitoring using HC-SR04 ultrasonic sensors, ensuring collision-free navigation. A modular communication architecture is developed, utilizing ESP01S for Wi-Fi connectivity and USART interfaces to interconnect three STM32 units, enabling remote control via a custom Android app developed with AppInventor. Additional functionalities include environmental monitoring via timer based input capture for temperature/humidity sensing and an I²C-driven OLED interface for real-time parameter visualization. Experimental results validate the system’s robustness in adaptive speed control, obstacle detection accuracy (<3 cm error), and low-latency wireless communication (<150 ms). The work demonstrates a cost-effective, scalable framework for smart home devices, balancing hardware efficiency with software flexibility. Future extensions could incorporate machine learning for path optimization or multi-robot coordination.
author2 Wang Qijie
author_facet Wang Qijie
Li, Jianming
format Thesis-Master by Coursework
author Li, Jianming
author_sort Li, Jianming
title STM32-based floor sweeping robot
title_short STM32-based floor sweeping robot
title_full STM32-based floor sweeping robot
title_fullStr STM32-based floor sweeping robot
title_full_unstemmed STM32-based floor sweeping robot
title_sort stm32-based floor sweeping robot
publisher Nanyang Technological University
publishDate 2025
url https://hdl.handle.net/10356/182894
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