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cs393r_starter

Using this Repo

You will be using a duplicate of this repo for all development in the class. This repo provides starter code for the ROS subscriptions, publishers and control loops you will be using.

Prerequisites

Please refer to the UT AUTOmata reference manual for instructions on setting up the dependencies:

Duplicate the Repo

  1. Make sure you're logged into your GitHub account.
  2. Create a new repo with the same name under your GitHub account. Dont initialize that with anything.
  3. git clone <this repository url> (found in the upper right)
  4. cd <cloned_repo>
  5. git push --mirror <your new repository url>

Clone and Build

  1. git clone <your repository url> (found in the upper right)
  2. After you have cloned the repo, add it to your ROS path by adding the following line to the end of ~/.bashrc:
    export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:[Local path to your repo]
    
    For example:
    export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/home/joydeepb/cs393r_starter
    
  3. Reload .bashrc so that the path is updated:
    source ~/.bashrc
    
  4. cd <cloned_repo>
  5. make -j

Code Overview

There are three main executables: navigation, particle_filter, and slam. Each executable has a corresponding .h and .cc file that defines the class for the implementation. An associated *_main.cc file abstracts away ROS-specific details. For example, the particle_filter executable consists of three files:

src
└── particle_filter
    ├── particle_filter.cc
    ├── particle_filter.h
    └── particle_filter_main.cc

Every header file includes documentation in comments for the variables and subroutines.
The project compiles with Eigen for linear algebra and coordinate geometry, the amrl_shared_lib for commonly used robotics subroutines, and a custom simple priority queue implementation. Some useful references on how to use the libraries:

Running the Code

Make sure you recompile your code between changes.

  • To run navigation:
    ./bin/navigation
    
  • To run the particle filter:
    ./bin/particle_filter
    
  • To run SLAM:
    ./bin/slam
    

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