Update readme

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)
@@ -21,7 +28,39 @@ 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.
+
+
 ## Installation
 ### Requirements
 Before starting, please ensure you have installed the following
@@ -36,8 +75,9 @@ 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`
+
+> Command :  
+> `pip install numpy colcon-common-extensions opencv-python pyrealsense2 cvbridge3 scikit-image`
 
 - $`\textcolor{red}{\text{[OPTIONAL]}}`$ Gazebo (for the simulation)
 -  $`\textcolor{red}{\text{[OPTIONAL]}}`$ Teleop twist keyboard (to control manually the robot)
@@ -55,7 +95,7 @@ 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
 ```
 
 
@@ -67,6 +107,8 @@ export ROS_AUTOMATIC_DISCOVERY_RANGE=SUBNET #Tell ROS to make your nodes only ac
 
 ### 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
@@ -102,8 +144,9 @@ 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**