Search and Sample Return Project

This project is modeled after the NASA sample return challenge and forked from Udacity's Robotics Nanodegree program, project 1.

My plan for this repository is for fulfillment of the challenge, and then further forking to create a dog-excrement search and retreival bot for my back yard.

The Simulator

The first step is to download the simulator build that's appropriate for your operating system. Here are the links for Linux, Mac, or Windows.

You can test out the simulator by opening it up and choosing "Training Mode". Use the mouse or keyboard to navigate around the environment and see how it looks.

Installing Anaconda, creating runtime environment, and executing

Overview

Using Anaconda consists of the following:

1. Install miniconda on your computer
2. Create a new conda environment using this project
3. Each time you wish to work, activate your conda environment

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Installation

Download the version of miniconda that matches your system. Make sure you download the version for Python 3.6.1

NOTE: There have been reports of issues creating an environment using miniconda v4.3.13. If it gives you issues try versions 4.3.11 or 4.2.12 from here.

	Linux	Mac	Windows
64-bit	64-bit (bash installer)	64-bit (bash installer)	64-bit (exe installer)
32-bit	32-bit (bash installer)		32-bit (exe installer)

Install miniconda on your machine. Detailed instructions:

• Linux: http://conda.pydata.org/docs/install/quick.html#linux-miniconda-install
• Mac: http://conda.pydata.org/docs/install/quick.html#os-x-miniconda-install
• Windows: http://conda.pydata.org/docs/install/quick.html#windows-miniconda-install

Setup your the Sample-Search-And-Retrieve environment.

git clone https://github.com/ergoego/Sample-Search-And-Retrieve.git  
cd RoboND-Python-StarterKit

If you are on Windows, rename
meta_windows_patch.yml to
meta.yml

Create Sample-Search-And-Retrieve. Running this command will create a new conda environment that is provisioned with all libraries you need to be successful in this program.
NOTE: if you get an error when you try to run this command that conda doesn't exist, try closing and re-opening your terminal window.

conda env create -f environment.yml

NOTE: If the above command fails due to internet issues or timed out HTTP request then remove the partially built environment using the following command (then run the above create command again):

conda env remove -n Sample-Search-And-Retrieve
conda env create -f environment.yml 

Verify that the Sample-Search-And-Retrieve environment was created in your environments:

conda info --envs

Cleanup downloaded libraries (remove tarballs, zip files, etc):

conda clean -tp

Installing OpenCV

The Udacity project this is forked from suggests installing miniconda with python==3.5.1, and specifying opencv3 in environment.yml, however this was giving me problems that moving to python==3.6.1 solved.

However, opencv3 no longer wanted to work with that version, so the workaround I came up with was to: remove opencv3 and change to python==3.6.1, build the environment, install pip in the environment, and then use pip in the environment to install opencv-contrib-python (opencv doesn't mantain a pip package for their library, so the open-source opencv-python-contrib is basically a mirror). I'm sure there is a way to have this done automatically when the environment is built and what I have done is by no means optimal.

So this boils down to:

conda install -n Sample-Search-And-Retrieve pip
activate Sample-Search-And-Retrieve
pip install opencv-contrib-python

Using Anaconda

Now that you have created an environment, in order to use it, you will need to activate the environment. This must be done each time you begin a new working session i.e. open a new terminal window.

Activate the Sample-Search-And-Retrieve environment:

OS X and Linux

$ source activate Sample-Search-And-Retrieve

Windows

Depending on shell either:

$ source activate Sample-Search-And-Retrieve

or

$ activate Sample-Search-And-Retrieve

That's it. Now all of the Sample-Search-And-Retrieve libraries are available to you.

To exit the environment when you have completed your work session, simply close the terminal window.

Uninstalling

If you ever want to delete or remove an environment

To delete/remove the "Sample-Search-And-Retrieve" environment:

conda env remove -n Sample-Search-And-Retrieve

Data Analysis

Included is the IPython notebook called Rover_Project_Test_Notebook.ipynb, which was used for initial prototyping and image analysis.

Navigating Autonomously

The file called drive_rover.py is what you will use to navigate the environment in autonomous mode. This script calls functions from within perception.py and decision.py. The functions defined in the IPython notebook are all included inperception.py. decision.py includes another function called decision_step(), which uses conditional statements evaluating the rover's state and the results of the perception_step() analysis to navigate autonomously.

Launch the program:

python drive_rover.py

Then launch the simulator and choose "Autonomous Mode".