Difference between revisions of "Tutorial"

From MAE/ECE 148 - Introduction to Autonomous Vehicles
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         priority=50
         priority=50
         id_str="ucsdrobocarlab"
         id_str="ucsdrobocarlab"
  }
    }


and follow the instructions for booting your Pi for the first time, including the section '''Setup Pi's Hostname'''.  
and follow the instructions for booting your Pi for the first time, including the section '''Setup Pi's Hostname'''.  

Revision as of 22:57, 13 October 2017

Build

Designing and fabricating a wheel based mobile robot vs. building on the top of a reliable platform such as an R/C truck 1/8 scale.

  • R/C Truck 1/8 Scale
  • Embedded system 4 cores Linux
  • 5 megapixel camera
  • Servo controller
  • Power management
  • LiPo Battery
  • Safety on LiPo charging, use, and storage
  • Wireless Emergency Off (EMO) circuit

Raspberry Pi Setup

Follow the instructions from:

http://docs.donkeycar.com/guide/install_software

to download an image that already contains all that you need to run the donkey car software.

Follow the instructions in Get the Raspberry Pi working.

This next step is very important. If you miss this configuration before you boot for the first time you will not be able to connect to your Pi using the lab network!

Substitute the content of the file /boot/wpa_supplicant.conf given in the section Setup the Pi's WiFi for first boot by the following:

   ctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev
   update_config=1
   country=US
   
   network={
       ssid="UCSDRoboCar2.4GHz"
       key_mgmt=WPA-PSK
       psk="UCSDrobocars2017"
       priority=60
       id_str="ucsdrobocarsfield"
   }
   
   network={
       ssid="UCSDRoboCar2.4GHz_lab"
       key_mgmt=WPA-PSK
       psk="UCSDrobocars2017"
       priority=50
       id_str="ucsdrobocarlab"
   }

and follow the instructions for booting your Pi for the first time, including the section Setup Pi's Hostname.

STOP do not run anything starting at Connecting to the Pi.

Track

  • Track building - hands-on ~ 40x20 m

Python

Open CV

ROS

Autonomous Vehicles

  • Odometry with wheels encoders and IMU
  • Short range obstacle avoidance using low cost ultrasonic sensors
  • Street light development RED/YELLOW/GREEN
  • Image processing with OpenCV
  • Image segmentation - far view, close view, fast processing