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self-driving-model-car using back-propagation neural network algotithm

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BPnetwork_smartcar

my project display

Devices:

  • Raspberry_pi3b+
  • NXP_smartcar game model
  • Computer

Dependencies:

  • Computer:

    • opencv3.4
    • Numpy
    • PiSerial
    • Pygame
  • Raspberry Pi:

    • Picamera
    • Piserual
  • model_car:

    • K60

Running:

  1. Run pi_stream.py in raspberr_pi firstly.
  2. Run computer_training_date_collect.py in the computer and use joy to control model_car to collet training_date.The date will be saved in a .npz file
  3. Run computer_mlp_training.py in the computer.The network_model will be saved in a .xlm file.
  4. Run computer_mydriver.py in the computer.The model_car should be run automatically

Note:

  • Here I only provide the core program on the car model, different people will use different objects to control.

  • Here we need to operate according to your actual situation.

  • You should download the code into car in advance and make sure your car can be controled by computer's command well

  • I set up communications between car and computer by using HC05 Bluetooth.

  • If your objects is similer to my model_car,and need all my code.you can download another repository NXP-K60.

  • Copy all the code files in the app folder here to the corresponding NXP-K60's directory

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