Ureed-Hussain

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Muhammad Ureed Hussain Ureed-Hussain

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I aspire to become a future researcher in the field of Computer Vision and Robotics, with a focus on solving real-world problems using robots.

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Ureed-Hussain/README.md

Muhammad Ureed Hussain

Vision and Robotics Engineer • ROS 2 • Motion Planning • Perception-to-Action

Robotics-first profile with strong vision foundations — focused on building reliable robot systems for real-world environments.

👋 About

📍 Le Creusot, France
🎓 VIBOT (Vision & Robotics) — European Master at
Université Bourgogne Europe (uB)
🏭 Industry Experience: full-time and part-time at
Wasoria
🔧 Current Internship (Industrial Robotics — FANUC): collaboration between
Wasoria and imVia Lab
Building a system to extract hazardous objects from a moving conveyor belt (robot integration, safety constraints, perception + control pipeline).

🔬 Research & Technical Focus

Robotics (primary): ground robots, industrial manipulators, mobile manipulation
Motion planning & control: MoveIt, trajectory generation, task-level autonomy
Robotics perception: perception-to-action pipelines, 2D→3D understanding for robots
Robot autonomy: mapping, localization, exploration, navigation (simulation → deployment)

📝 Publication

Design and Development of Assistive Ankle Exoskeleton for Rehabilitation using Electromyography
IEEE Xplore: https://ieeexplore.ieee.org/abstract/document/10465823

🛠️ Tech Stack

Languages

Robotics

Vision / ML (supporting)

Tools

🧠 Selected Work

A few projects I find especially interesting — many more projects are available in my repositories.

1) Industrial / Manipulators

(Ongoing) Internship focus (FANUC): hazardous object extraction from a moving conveyor belt (integration + safety + execution)

2) Mobile Robotics

Real-Time Virtual Obstacle Mapping (Simulation): https://github.com/Ureed-Hussain/Real-Time-TurtleBot3-Virtual-Obstacle-Mapping-Localization-In-Simulation
Autonomous Frontier Exploration (ROS 2 Humble): https://github.com/Ureed-Hussain/Autonomous-Frontier-Exploration-with-RRT-in-ROS-2

3) Vision / Perception

Incremental SfM Pipeline: https://github.com/Ureed-Hussain/incremental-sfm-pipeline
ROS 2 Monocular Depth + 3D Reconstruction: https://github.com/Ureed-Hussain/ros2-monocular-depth-yolov8-reconstruction

4) Deep Learning

Traffic Sign Detection (Faster R-CNN, PyTorch): https://github.com/Ureed-Hussain/traffic-sign-detection-faster-rcnn
Self-Organizing Map (SOM) Time-Series Classification: https://github.com/Ureed-Hussain/Kohonen-Self-Organizing-Map--SOM-

📫 Contact

📧 Email: [email protected]
💼 LinkedIn: https://www.linkedin.com/in/muhammad-ureed-hussain-86947219b/
🧑‍💻 GitHub: https://github.com/Ureed-Hussain

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Real-Time-TurtleBot3-Virtual-Obstacle-Mapping-Localization-In-Simulation Real-Time-TurtleBot3-Virtual-Obstacle-Mapping-Localization-In-Simulation Public

Real-time lane-based mapping, localization, and navigation on a physical TurtleBot3 using ROS 2, camera calibration, SLAM, and virtual corridor generation.

Python 2 1
Autonomous-Frontier-Exploration-with-RRT-in-ROS-2 Autonomous-Frontier-Exploration-with-RRT-in-ROS-2 Public

This project implements an autonomous exploration system for turtlebot3 robots using frontier-based exploration and RRT (Rapidly-exploring Random Tree) in ROS 2 (Humble).

Python 1
traffic-sign-detection-faster-rcnn traffic-sign-detection-faster-rcnn Public

This project serves as a baseline, which I will use to compare with my other detection models.

Jupyter Notebook 1
incremental-sfm-pipeline incremental-sfm-pipeline Public

Forked from hassaanahmed04/sfm

Makefile 1
ros2-monocular-depth-yolov8-reconstruction ros2-monocular-depth-yolov8-reconstruction Public

ROS 2–based monocular 3D perception system using YOLOv8 and MiDaS for real-time object detection, depth estimation, and 3D point cloud generation from a single Raspberry Pi camera.

Python 2 1
turtlebot3-line-follower-yolov8-stop-sign turtlebot3-line-follower-yolov8-stop-sign Public

ROS 2 TurtleBot3 line following with STOP sign detection using OpenCV and YOLOv8 in Gazebo simulation.

Python 1