Object-Tracking and Obstacle-Avoiding Mobile Robot

dc.contributor.authorHeraiz Osema
dc.contributor.authorChadi Mohamed
dc.contributor.authorRapporteur/ Djalab Abd Elhak
dc.date.accessioned2026-01-21T08:45:47Z
dc.date.issued2025
dc.description.abstractThis project presents the design and implementation of an autonomous mobile robot capable of tracking a predefined path and avoiding obstacles in real time. The system is built using an Arduino Uno microcontroller, DC motors driven by an L298N H-bridge module, and a combination of ultrasonic and infrared (IR) sensors for environmental perception. The ultrasonic sensor is responsible for detecting obstacles in the robot’s path, while the IR sensors enable line-following and side detection functionalities. The robot's behavior is controlled by a decision-making algorithm embedded in the Arduino, which processes sensor data and commands the motors accordingly to ensure smooth navigation. Servo-controlled scanning is also integrated to improve environmental awareness. Simulation of the hardware circuit was conducted using Cirkit Designer to validate the wiring and logic before physical assembly. Testing was performed in a controlled environment with various obstacle configurations and line paths. Results indicate high reliability in obstacle detection and path correction, with quick reaction times and stable motor control. This low-cost and adaptable solution can serve as a foundation for more advanced autonomous systems used in smart vehicles, warehouse automation, and educational robotics.
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/48143
dc.language.isoen
dc.publisherUniversity of Msila
dc.subjectObstacle-Avoiding Mobile Robot
dc.titleObject-Tracking and Obstacle-Avoiding Mobile Robot
dc.typeThesis

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Memoire Masterinst Heraiz Osema Chadi Mohamed.pdf
Size:
1.73 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:

Collections