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UCSD IEEE Project Drive (Sparkfun AVC) for 2016/17. This repository includes codes for programming a fully autonomous vehicle that can map and navigate any given flat environment through the implementation of ROS and OpenCV. [ WORK IN PROGRESS ]

Python 7.33% CMake 9.06% C++ 35.70% Arduino 41.66% C 5.35% Shell 0.90%

projectdrive16_17's Introduction

UCSD Project Drive 2016/17 - [ WORK IN PROGRESS ]

Project Drive is a year long student run project hosted and funded by the IEEE Branch of the University of California, San Diego. The premise of this project is to build a 1/10 scale fully autonomous RC vehicle that will compete in this year's 2017 SparkFun Speed Demons Autonomous Vehicle Competition.

For this year's competition, the team will be focusing on designing and implementing a vehicle that could explore and map out any given flat environment. We therefore will be building our own 360 LIDAR system which would be used for spatial mapping and localization in conjunction with ROS's Hector SLAM. We will also be working with OpenCV to implement various image recognition softwares that will further allow our vehicle to interact with its environment by picking up both obstacles and goal points scattered throughout the race course.

Progress Update

Brief Update

As of March 31st, 2017, the team currently has spatial mapping and localization up and running while our 360 LIDAR system is stationary. We have fully completed designing and testing our power system that will ensure power is delivered to all the components of our vehicle in a safe and reliable manner. Our next step would be to attach the power system to our vehicle and begin testing spatial mapping while the 360 LIDAR system is in motion.

As of May 31st, 2017, the team has successfully mapped out small hallways while the vehicle is in motion. The picture of the map is shown below. However, we are having some difficulties getting reliable distance reading from obstacles/walls that are further away due to the slower refresh rate of our sensor. As a result, we are looking into using an IMU and odometer to help increase the accuracy of SLAM.

PICTURE

Full Progress Report

360 LIDAR System And SLAM

We are currently using the TeraRanger One as the distance sensor for our 360 LIDAR system. The middle and right image shows the resulting map we received from running our sensor at 300 Hz vs 1000 Hz. PICTURE

Video Demonstration

Website

At the present time, our primary focus is to complete the project in time for the competition in September 2017. However, we are documenting all our design process in detail and are excited to share it with you in a comprehensive website in the future. Stay tune!

Contact Us

Team Lead

  • Peter Mai - p1mai [at] ucsd.edu

Software Team

  • Shirley Han - smh022 [at] ucsd.edu
  • Jason Ma - jam043 [at] ucsd.edu
  • William Ma - wim001 [at] ucsd.edu
  • Peter Mai - p1mai [at] ucsd.edu

Electrical Team

  • Jason Kelley - jkelley [at] ucsd.edu
  • Noah Chung - mwchung [at] ucsd.edu

CAD Team

  • John (Jack) Wheelock - jwheeloc [at] ucsd.edu

projectdrive16_17's People

Contributors

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Watchers

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