Robomanics
Document register
- Poster1 pagePublished
- Presentation videoYouTubePublished
- Bill of materials1 pagePublished
- Team description paperNot shared
- Engineering journalNot shared
- Source code6 KB · GitHubPublished
Sharing each document is the team's decision. “Not shared” means this team chose not to publish it, or did not submit one — not that it is missing from the archive.
In their words
Robomanics is an autonomous rescue simulation robot designed to explore unknown environments, detect victims, solve cognitive targets, and safely return to its starting position. The system is developed in Python and follows a modular architecture consisting of perception, decision-making, and motion-control layers.
The robot continuously collects data from GPS, IMU, LiDAR, distance sensors, and RGB cameras to build an occupancy-grid representation of the environment. This map is used to identify walls, obstacles, holes, checkpoints, and unexplored areas. Using autonomous path-planning and navigation algorithms, the robot efficiently explores the arena while dynamically adapting to environmental changes and handling recovery situations when navigation difficulties occur.
For victim detection, the robot processes camera images to identify and classify rescue symbols, determine their locations, and report them accurately. In addition, a dedicated cognitive target detection module recognizes circular targets, extracts ring colors, converts them into numerical values, and classifies the target according to competition requirements.
What distinguishes Robomanics is the integration of mapping, victim detection, cognitive target recognition, autonomous exploration, and recovery mechanisms into a unified decision-making framework. This allows the robot to operate efficiently in complex environments while maintaining reliable performance, accurate reporting, and complete mission execution from exploration to safe return.
Poster
Read the text of this document — 168 words
!
Robomanics
Egypt | Rescue Simulation
ll o eam
He nd
T
f ou ics!
I m an
o
Rob
Meet The Team
participa
ted
in Nation
al
RoboCup
2025 and
achieved
Ziad ElGa 2nd Plac
mal e
Fareeda Mapping
Navigati
Hossam
o n & Dete
ction La i l a E l h
Navigati adidy
on & Det
ection
Team Leadership
Coach:
Dr. Amal Mehanna
Co-Coach:
AL. Ibrahim Tagen
Meet The Robot
Flow Chart
Programming
Language
Start Program
Initialize Robot Sensors
Initialize Map and Variables
Main Loop Starts
Python
Read Sensors
Update Robot Position
Path Planning Algorithm
Mapping Algorithm
Mapping Algorithm
NO
Choose Next Movement
Victim or
Cognitive Move Robot
Target
Detected?
YE
S
All Reachable
NO
Start Program Areas
Explored?
Initialize Robot Sensors
NO
YES
Initialize Map and Variables Plan Path Back to Start
Main Loop Starts Return to Starting Tile
Check Obstacles, Holes, Swamps Send Exit Command
Occpancy Grid
Is Robot Map (Real-
Stuck? Time)
S
YE
Call Lack of Progress / Recover End Program
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Presentation video
Hosted on YouTube. The player loads only when you press play.
Bill of materials
Read the text of this document — 154 words
Name of the Total Cost Total Cost ($)
Team name: Robomanics Local Currency Local Currency U.S.A. Dollars
Brazilian Real R$0.00 $0.00
# Name Software's Tool/Library Description Source Autor Cost (Local Cost (USA
1 Python Software Tool Main programming language https://python.org Python Software FREE FREE
2 Webots Software Tool Robot simulation environment https://cyberbotics.com Cyberbotics FREE FREE
3 YOLO Library Victim detection model https://ultralytics.com Ultralytics FREE FREE
4 OpenCV Library Computer vision and image processing https://opencv.org OpenCV Team FREE FREE
5 NumPy Library Numerical computing and matrix operations https://numpy.org NumPy Developers FREE FREE
6 Matplotlib Library Visualization and debugging https://matplotlib.org Matplotlib Team FREE FREE
7 Visual Studio Code Software Tool Development environment https://code.visualstud Microsoft FREE FREE
8 GitHub Software Tool Version control and collaboration https://github.com GitHub Inc. FREE FREE
9 LiDAR Sensor (Simulated) Simulation Component Virtual LiDAR for mapping Webots Cyberbotics Included Included
10 GPS/IMU Sensors (Simulated)S imulation Component Localization and orientation Webots Cyberbotics Included Included
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Source code
The team's own source code, 6 KB. It is a download rather than part of this page, because a zip is something you open on your computer. It comes from GitHub, which some school networks block.