FS-ARMCar is an intelligent omnidirectional mobile platform launched by Beijing Huaqing Yuanjian Education Technology Co., Ltd. for university teaching and research. This platform includes an omnidirectional vehicle robot with a robotic arm and a training application site, which can be used for embedded teaching in universities, skill competitions in colleges and universities, and other occasions.

1. Modularization

FS-ARMCar consists of aluminum alloy connectors, drive modules, core control modules, robotic arms, machine vision units, and power modules, which are assembled through aluminum columns, hand screws, and nuts.

2. Multi platform

The underlying structure and driver part of FS-ARMCar support multi platform access. The Cortex-M4 core unit is responsible for overall control and scheduling, with the main development language being C/C++. The machine vision recognition unit is responsible for image acquisition and analysis, with rich interfaces and a main development language of MicroPython. The machine vision recognition unit reduces the difficulty of machine vision related development and can quickly build applications through MicroPython language.

3. Fun

The robotic arm, omnidirectional mobile platform, and machine vision recognition unit equipped on FS-ARMCar can complete some learning related to embedded robots, greatly reducing development difficulty and adapting to the related learning of microcontroller development, automatic control, machine vision, and primary artificial intelligence. Motivate developers with robot related components to better understand robot courses.

4. Openness

The FS-ARMCar system software and hardware are both open architecture, and customers can expand and develop them according to their own needs. All code, systems, and algorithms are open source.

5. Intelligentization

FS-ARMCar can complete tracking, grabbing, and handling related tasks such as color recognition, barcode recognition, and shape recognition through an omnidirectional mobile platform, sensors, a 6-degree-of-freedom robotic arm, and a machine vision recognition unit.

6. Wide adaptability range

A complete set of routine development, guidance materials, all sensors and development documents required for intelligent robots, suitable for undergraduate and vocational teaching, and can also be used as a research platform for graduate students to conduct research projects.

1. Cortex-M4 development platform experiment

Development environment setup; STM32CubeMX application; GPIO input/output experiment; SysTick system tick experiment; UART serial port data transmission and reception experiment; Universal timer counting experiment; Orthogonal code wheel input capture experiment; PWM DC motor drive experiment; A/D analog-to-digital conversion experiment; I2C bus driver experiment; SPI serial peripheral design; Direct Memory Access Experiment (DMA); FLASH data storage experiment; PID regulation control experiment; MPU6050 internal DMP firmware migration analysis; OLED display experiment; MPU6050 driver experiment; QMC5883L driving experiment; ESP-32S WiFi transparent transmission experiment;

2. Machine vision section

Development environment setup; Basic Python syntax; Turn on the LED light; Serial communication experiment; Facial detection experiment; Pupil recognition experiment; Color tracking experiment; Tag tracking experiment; Barcode recognition experiments, etc;

3. Mechanical arm section

Development environment setup; STM32CubeMX application; GPIO input/output experiment; SysTick system tick experiment; UART serial port data transmission and reception experiment; Mechanical arm control experiments, etc;

4. Programming of marker units

Development environment setup; STM32CubeMX application; Familiar with WiFi module AT commands; PWM driven RGB color lights;

5. Android side experiment

Android development environment setup; Intelligent vehicle development process; Detailed explanation of intelligent vehicle application development; 6-degree-of-freedom robotic arm control;