Mobile Robot Control 2023 Rosey: Difference between revisions

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=== Global Navigation ===
===Global Navigation===
We were inspired by the lecture about Safe navigation in a hospital environment to introduce some context-aware navigation into our model, by means of semantics.  
'''Used algorithm and predefined knowledge'''
 
The global navigation uses the A* algorithm to find the shortest path to from a starting node to a goal node. The A* algorithm uses a predefined grid of nodes. This grid is applied by a JSON file, generated with Matlab. With Matlab, the grid nodes with their connections are manually chooses in the known map. On top of that, we were inspired by the lecture about Safe navigation in a hospital environment to introduce some context-aware navigation into our model, by means of semantics. Each node contains some semantic information about its environment, described by a integer. The following semantic integers are included: 0 = table 0, 1= table 1, ..., 49 = table 49, 50 = door, 99 = empty (meaning no semantic information present). This information is also included in the JSON file
 
'''Initiation phase (run once)'''
 
The json file is imported with the <code>loadConfigFile()</code>and the grid is constructed with<code>constructGrid()</code>.
 
 
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=== Local Navigation ===
===Local Navigation===




=== Localisation ===
===Localisation===

Revision as of 15:44, 21 June 2023

Welcome to the group page of team Rosey!

Group members table

Group members of team Rosey
Name Student ID
Eline Wisse 1335162
Lotte Rassaerts 1330004
Marijn Minkenberg 1357751
Rainier Heijne 1227575
Tom Minten 1372300
Lowe Blom 1266020

Midterm presentation

File:Midterm presentation Rosey.pdf

Current state diagram

Current state diagram, reflected in the main.c file. (old version as of 17-06-2023)

File structure

Current file structure. Arrows indicate includes.

Work division

We identified three 'major parts' of the assignment. These are the localisation, the global and local navigation of the robot. We additionally saw use for an overseeing role, which should ensure that the interfaces between the functions are clear. The work is divided as follows:

  • Marijn : System architecture & overview
  • Tom : Global navigation (A*)
  • Eline & Rainier : Local navigation (potential fields + open space)
  • Lowe & Lotte : Localisation


Global Navigation

Used algorithm and predefined knowledge

The global navigation uses the A* algorithm to find the shortest path to from a starting node to a goal node. The A* algorithm uses a predefined grid of nodes. This grid is applied by a JSON file, generated with Matlab. With Matlab, the grid nodes with their connections are manually chooses in the known map. On top of that, we were inspired by the lecture about Safe navigation in a hospital environment to introduce some context-aware navigation into our model, by means of semantics. Each node contains some semantic information about its environment, described by a integer. The following semantic integers are included: 0 = table 0, 1= table 1, ..., 49 = table 49, 50 = door, 99 = empty (meaning no semantic information present). This information is also included in the JSON file

Initiation phase (run once)

The json file is imported with the loadConfigFile()and the grid is constructed withconstructGrid().



Local Navigation

Localisation