From MAE/ECE 148 - Introduction to Autonomous Vehicles
Revision as of 09:45, 11 June 2019 by Spring2019Team3 (talk | contribs) (Mechanical)
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The goal of our project is to follow a person using IR sensors. Under real world circumstances, the concept of our project can be applied to indoor self-following shopping cart system for supermarkets. The car can follow a person who has an IR LED patch attached at a certain range.

Team Members

Jose Manuel Rodriguez - ME

Yuan Chen - ME

Jason Nan - BENG: BSYS

Po Hsiang Huang - EE


Plate and Camera Mount
The camera is designed to be adjustable and can be easily locked in place with a screw and a nut. During our training, we need to find the optimal camera angle thus making the camera stand adjustable saved us a lot of time. The stand for the Structure Sensor is set to 30 degree of inclination since the camera itself has a wide range of view of 160 degrees and it needs to capture the IR patch that is attached to the back of a person. The Acrylic platform is printed with Laser-cut machine. Multiple mounting holes are cut for variety of mounting hardware choices if applicable.
File:Camera mount1.jpg
3D printed camera mount for the pi-camera
3D printed camera mount for Structure Sensor
3D printed housing for Raspberry Pi
Circuit Diagram
Below is the circuit diagram for the robot car setup. A emergency stop circuit is used using a relay which can be remotely controlled. This adds extra safety during the test and training. Two LEDs are used to indicating the connection. Blue means circuit is connected and the car can be controlled by the controller, and red means circuit is cut-off.

Autonomous Driving

Indoor Circuit
Here is a video of 7 laps of indoor driving
Outdoor Circuit
Here is a video of 3 laps of outdoor driving


Target Following using Structure Sensor
Neural Network
IR Patch
Integrate to Donkey Framework