Merge pull request #93 from BPLA-Team/update_readme

Update README.md

Author: Stargazer2005

.extra/images/program_works.png

@@ -4,27 +4,33 @@
   <img src=".extra/images/icon.png" alt="Logo" width="80" height="80">
 </div>
 
-**Project of four first grade MIPT DAFE/RSE students (for engineering practical work in the second semester) in Qt C++**
+**Project of four first grade MIPT AES DAFE students (for engineering practical work in the second semester) in Qt C++**
+
+<div align="center">
+  <img src=".extra/images/program_works.png" alt="Program">
+</div>
 
 ## Documentation
 
-Project's [documentation](https://bpla-team.github.io/locus_no_pilotus/index.html) generated with Doxygen with [convenient CSS theme](#used-libs-and-sources).
+Project's [documentation](https://bpla-team.github.io/locus_no_pilotus) generated with Doxygen with [convenient CSS theme](#used-libs-and-sources).
 
 # Contents
 
 - [Description](#description)
 - [Installation and configuring](#installation-and-configuring "with using MSYS")
 - [Used libs and sources](#used-libs-and-sources "we are using GitHub submodules feature 😎")
 - [Authors](#authors "the best guys")
-- [Presentation](#presentation "video link")
 
 ## Description
 
 In this project, we are developing an application that calculates the trajectory of a flying delivery robot that collects valuable cargo from control points: **Targets**.
 On its way, it may encounter high mountains that it cannot fly over: **Hills**; or elliptical territories that are impossible to visit due to climate conditions: **TrappyCircles**.
 Also, through some control points, the robot is simply unable to move, as the cargo may not be ready for transportation at that time, these are **TrappyLines**.
 
-The robot's trajectory is calculated using several mathematical algorithms: [...].
+The robot's trajectory is calculated using several mathematical algorithms: Little's Algorithm (solving the Traveling Salesman Problem (TSP) for multiple robots), Dijkstra's Algorithm (finding the shortest path between two points in a graph), Geometric Algorithms for Obstacle Handling (tangents to circles and polygons and intersection checking), Visibility Graph Construction, Composite Trajectory Planning Algorithm.
+
+This is a comprehensive system that combines geometric computations with optimization algorithms to solve complex trajectory planning problems in the presence of obstacles. The algorithms work together to find collision-free paths that minimize total travel distance while visiting all required points.
+
 The graphical interface for constructing the trajectory was created using [Qt](#used-libs-and-sources) and [QCustomPlot](#used-libs-and-sources).
 
 In the application, you can add objects using window forms, interact with the trajectory calculation plot using the mouse cursor, create and open files in `.json` format with a specific style for this application. Editing objects can also be done with cursors or using a special dynamic input field with tables, opened in a separate window mode or embedded in the main one.

README.md

@@ -8,22 +8,29 @@
  * @section description Description
  * In this project, we are developing an application that calculates the
  * trajectory of a flying delivery robot that collects valuable cargo from
- * control points: Targets. On its way, it may encounter high mountains that
- * it cannot fly over: Hills; or elliptical territories that are impossible
- * to visit due to climate conditions: TrappyCircles. Also, through some
+ * control points: **Targets**. On its way, it may encounter high mountains that
+ * it cannot fly over: **Hills**; or elliptical territories that are impossible
+ * to visit due to climate conditions: **TrappyCircles**. Also, through some
  * control points, the robot is simply unable to move, as the cargo may not be
- * ready for transportation at that time, these are TrappyLines.
+ * ready for transportation at that time, these are **TrappyLines**.
  *
  * The robot's trajectory is calculated using several mathematical algorithms:
- * [...]. The graphical interface for constructing the trajectory was created
- * using Qt and QCustomPlot.
+ * Little's Algorithm (solving the Traveling Salesman Problem (TSP) for multiple
+ * robots), Dijkstra's Algorithm (finding the shortest path between two points
+ * in a graph), Geometric Algorithms for Obstacle Handling (tangents to circles
+ * and polygons and intersection checking), Visibility Graph Construction,
+ * Composite Trajectory Planning Algorithm.
+ *
+ * This is a comprehensive system that combines geometric computations with
+ * optimization algorithms to solve complex trajectory planning problems in the
+ * presence of obstacles. The algorithms work together to find collision-free
+ * paths that minimize total travel distance while visiting all required points.
  *
  * In the application, you can add objects using window forms, interact with the
  * trajectory calculation plot using the mouse cursor, create and open files in
- * .json format with a specific style for this application. Editing objects can
- * also be done with cursors or using a special dynamic input field with tables,
- * opened in a separate window mode or embedded in the main one.
- *
+ * `.json` format with a specific style for this application. Editing objects
+ * can also be done with cursors or using a special dynamic input field with
+ * tables, opened in a separate window mode or embedded in the main one.
  */
 
 // Qt libs: