KEYWORDS: Design and modelling, Control systems, Angular velocity, Sensors, Motion controllers, Transportation, Connectors, Clocks, Surgery, Process control
With the development of the times, intelligence has become more and more the theme of the era, and intelligent mobile devices are more applicable to various production and living in society. In order to reduce costs, increase applicability, and improve performance, this project designs a two-wheeled self-balancing scooter simulation. The scooter uses the STM32F103 chip as the main controller, uses the MPU-6050 to collect the tilt angle and motion speed of the vehicle body, and uses the PID algorithm to control the state of the vehicle body. The PID algorithm uses the given speed and calculates the acceleration through proportional, integral and differential three variables; then it controls the motion of the DC motor through the driver chip. The DC motor feeds back the speed to the main chip through the encoder to achieve self-balancing of the two-wheeled scooter when powered on. This design can also connect to a mobile APP through a Bluetooth module to control the movement of the scooter.
Compared with traditional contact-based gesture recognition systems, non-contact gesture recognition systems not only have good recognition performance, but also have advantages such as human-computer interaction, ease of use, and time and effort savings. This design is an intelligent non-contact gesture recognition device that uses the PAJ7620 sensor to collect gesture information. The embedded microcontroller identifies different gestures and displays different patterns through LED marquees, and provides voice prompts through a voice broadcast device. To improve visibility, this design also uses a TFTLCD liquid crystal display to display different gestures, and switches between gesture recognition mode and distance detection mode through four independent keys.
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