PyTorch Python Neural Network Autonomous 1/10 Car for Nvidia Jetson Nano
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System Hardware
- Servo Driver https://www.amazon.com/dp/B014KTSMLA/ref=cm_sw_r_tw_dp_U_x_.PW4CbAD5YKP4
- Jetson Nano https://developer.nvidia.com/embedded/jetson-nano-developer-kit
- Camera https://leopardimaging.com/product/li-imx219-mipi-ff-nano/
- Wifi Chip https://www.amazon.com/gp/product/B01MZA1AB2/ref=ppx_yo_dt_b_search_asin_title?ie=UTF8&psc=1
- Wifi Attenna https://www.arrow.com/en/products/2042811100/molex
- PS4 Controller https://www.amazon.com/dp/B01LWVX2RG/ref=cm_sw_r_tw_dp_U_x_USW4CbEXZK23G
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Car
- 1/10 4wd Car chassis https://www.amazon.com/dp/B00NYR8D1O/ref=cm_sw_r_tw_dp_U_x_zIW4Cb721TVKE
- Brushed Motor https://hobbyking.com/en_us/540-6527-brushed-motor-90w.html
- Standard Analog Servo https://hobbyking.com/en_us/hobbykingtm-hk15138-standard-analog-servo-4-3kg-0-17sec-38g.html
- 45A Brushed Car ESC https://hobbyking.com/en_us/hobbyking-x-car-45a-brushed-car-esc.html
- 5000mAh 2S 7.4V 60C https://hobbyking.com/en_us/turnigy-5000mah-2s-7-4v-60c-hardcase-pack-roar-approved.html
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Accessories
Install python requirements. Install ds4drv and connect PS4 Bluetooth controller to Ubuntu. Inside AutoCarJetsonNano/car, start main.py and drive car around. Images are captured when speed is > 0. After driving car around, offload images to remote computer for training and copy control_data.csv . Start autocar via Jupyter Lab or Notebook and train model via pytorch. Load model back to Nano after training and start main.py Press X to launch autopilot.
