Update README.md

README.md

-# group Astro, repository for the UV LARM
----
-## Authors :
-Inès El Hadri
+# Astro Group's repository for the LARM UV
+
+
+## Authors
+Inès El Hadri  
 Lucas Naury
 
----
+--- 
 ## Introduction
 This repository is a ROS2 package that allows the control of a kobuki robot. 
+
 ### Table of Contents :
 
 1. [Authors](#authors)
 1. [Introduction](#introduction)
+1. [How it works](#how-it-works)
+    1. [Goal](#goal)
+    1. [Expected behaviour](#expected-behaviour)
+    1. [Additional functionality](#additional-functionality)
 1. [Installation](#installation)
     1. [Requirements](#requirements)
     1. [Install the package](#install-the-package)
+    1. [Tune the camera HSV](#tune-the-camera-hsv)
     1. [Build the package](#build-the-packages)
 1. [How to use the package](#how-to-use-the-package)
     1. [In simulation](#in-simulation)
@@ -21,11 +28,46 @@ This repository is a ROS2 package that allows the control of a kobuki robot.
     1. [Visualization](#visualization)
 1. [Frequently Asked Questions](#faq)
 
+
+
+
 ---
+## How it works
+
+### Goal
+
+The goal is to explore a closed area (i.e. an area bounded with obstacles) with the robot while avoiding obstacles. While doing so, we must determine the number and position of green painted bottles.
+
+### Expected behaviour
+
+- The robot moves **continuously** in the area by **avoiding obstacles**
+    - If there are no obstacles, it moves straight
+    - If an obstacle is in front, it turns the opposite direction until there's no obstacle left in front. 
+- Using the **SLAM algorithm** with data from the LiDAR and the odometer, the robot builds a map and localizes itself in it.
+- Using a RealSense RGBD camera (D435i), the robot is able to **detect the green bottles**. Messages are sent in topics:
+    - `detection` : to state the detection
+    - `bottle_relative_pos` : to tell the position of the bottle relative to the camera
+    - `bottle_marker` : to mark the position of a bottle on the map
+- Experiments can be performed with **2 computers**:
+    - one on the robot (Control PC) running all the robot, movement and vision nodes
+    - a second for visualization and human control (Operator PC)
+
+### Additional functionality
+
+- An [**automatic HSV tuner script**](#tune-the-camera-hsv) allows you to calculate the ideal threshold to mask your bottle
+- Most configuration variables (robot speeds, bounding boxes, are set as **ROS parameters** so that they can be modified
+- The robot stops moving when you press any of the **3 robot buttons**. If you press it again, movement will continue.
+> All other data is still being processed when the robot is in pause
+- The robot **stops when you lift it** (i.e. the wheels are "falling"). It you put the robot back on the ground, movement will continue.
+
+In this branch, you'll also find a node that **automates the map discovery** (by sending goal poses to unknown areas for the robot to go to).
+> This has only been tested on the simulator, since we didn't have time to test it on the real robot
+
 ## Installation
 ### Requirements
 Before starting, please ensure you have installed the following
 - ROS2 Iron : https://docs.ros.org/en/iron/index.html
+- ROS2 packages : `apt install ros-iron-slam-toolbox ros-iron-nav2-bringup`
 - Python 3.10 : https://www.python.org/downloads/
 - Python packages :
     * math, os, signal, sys, time (installed with python)
@@ -36,10 +78,11 @@ Before starting, please ensure you have installed the following
     * cvbridge3
     * scikit-image
 </br>
-    >Command :  
-    >`pip install numpy colcon-common-extensions opencv-python pyrealsense2 cvbridge3 scikit-image`
 
-- $`\textcolor{red}{\text{[OPTIONAL]}}`$ Gazebo (for the simulation)
+> Command :  
+> `pip install numpy colcon-common-extensions opencv-python pyrealsense2 cvbridge3 scikit-image`
+
+- $`\textcolor{red}{\text{[OPTIONAL]}}`$ Gazebo (for the simulation) (`apt install ros-iron-gazebo-ros-pkgs`)
 -  $`\textcolor{red}{\text{[OPTIONAL]}}`$ Teleop twist keyboard (to control manually the robot)
 
 ### Configuration
@@ -55,18 +98,20 @@ export ROS_AUTOMATIC_DISCOVERY_RANGE=LOCALHOST #Tell ROS to make your nodes only
 However, if you want to be able to visualize data from another computer on the same network, add :
 
 ```
-export ROS_AUTOMATIC_DISCOVERY_RANGE=SUBNET #Tell ROS to make your nodes only accessible by the same machine
+export ROS_AUTOMATIC_DISCOVERY_RANGE=SUBNET #Tell ROS to make your nodes accessible by machines on the same network
 ```
 
 
 ### Install the package
 1. Open the command prompt in the ROS2 workspace directory
-1. Clone the IMT Tbot packages : `git clone https://bitbucket.org/imt-mobisyst/pkg-tbot/src/master/`
+1. Clone the IMT Tbot packages : `git clone https://bitbucket.org/imt-mobisyst/pkg-tbot.git` and `git clone https://bitbucket.org/imt-mobisyst/pkg-tsim.git`
 1. Clone this repository : `git clone http://gvipers.imt-nord-europe.fr/ines.el.hadri/larm.git`
 
 
 ### Tune the camera HSV
 
+To tune the HSV threshold parameters for the camera mask, we will use a script to automate it.
+
 First, put a bottle in front of the robot.
 
 Then, go in the `larm` directory and launch the HSV tuner python script using the following command
@@ -83,7 +128,7 @@ A window will popup with a frame from the RealSense camera :
 
 ### Build the packages
 In the same ROS2 workspace directory:
-- `./master/bin/install`
+- `./pkg-tbot/bin/install`
 - `colcon build`
 - `source install/setup.sh`
 
@@ -97,18 +142,27 @@ First, go in the ROS2 workspace.
 To launch the challenge 1 in **simulation**, run the following command :
 `ros2 launch grp_astro simulation_launch.yaml`
 
+If you want to launch the **automatic discovery nodes**, run the following command instead :
+`ros2 launch grp_astro auto_simulation_launch.yaml`
+
 ### On the tbot
 To launch the challenge 1 on the **real turtlebot**, run the following command :
 `ros2 launch grp_astro tbot_launch.yaml`
 
 ### Visualization  
-In parallel, if you want to **visualize** the information that is published on the different topics, you can run
-`ros2 launch grp_astro visualize.launch.py`
+In parallel, if you want to **visualize** the information that is published on the different topics, you can run :
+- `ros2 launch tbot_operator_launch.yaml` for the real robot
+- `ros2 launch sim_operator_launch.yaml`  in simulation
 
 > If you want to run this visualization on another computer than the one running the robot, make sure :
 > - they are on the **same network**
 > - they have the same **`ROS_DOMAIN_ID`** environment variable
 > - they have configured **`ROS_AUTOMATIC_DISCOVERY_RANGE=SUBNET`** in the environment variables
 
+
+
+If you want to launch the **automatic discovery visualizer** (path found, goal poses...), run the following commands instead :
+- `ros2 launch auto_sim_operator_launch.yaml`  in simulation
+
 ---
 ## FAQ