Qbot: Autonomous 3D Object Scanner & Mapper

📌 Project Overview

This project features a ROS 2 based differential-drive robot (Qbot) designed to autonomously identify, approach, and orbit a target object in a simulated environment. As it executes a precision orbit, it uses an onboard RGBD camera to generate a rich 3D Point Cloud of the object while simultaneously using a 2D LiDAR to map the surrounding room via SLAM.

🎯 Key Features

• Autonomous Target Tracking: Uses planar 2D LiDAR data to locate the target object while ignoring background walls using spatial filtering.
• Precision Orbiting: Implements proportional control to maintain a perfect orbital radius based on the camera's Vertical Field of View (FOV) and the object's height.
• 3D Point Cloud Generation: Captures high-fidelity spatial data using an RGBD sensor to recreate the 3D object in RViz.
• Auto-Termination Logic: Integrates angular velocity over time to track laps, automatically halting the robot after completing exactly 3 full orbits.
• Simultaneous 2D Mapping: Runs slam_toolbox asynchronously to generate a 2D occupancy grid of the environment during the scanning process.

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👥 Team Members

• Dineth Sankalpa
• Sanjuna Rathnamalala
• Binara Herath

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📷 System Visualization

Above: The captured 3D point cloud of the target object visualized in RViz during the autonomous orbiting phase.

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🛠️ Prerequisites

To run this simulation, you need the following installed on an Ubuntu 22.04 system:

• ROS 2 Humble
• Ignition Gazebo (Fortress or newer)
• ROS 2 Packages:

  sudo apt install ros-humble-ros-gz-bridge
  sudo apt install ros-humble-ros-gz-sim
  sudo apt install ros-humble-slam-toolbox
  sudo apt install ros-humble-xacro
  

🚀 Build & Installation

1. Clone the repository: git clone https://github.com/IntellisenseLab/final-project-slam.git cd Qbot--3D-object-mapping/simulation

2. Build the workspace: colcon build --symlink-install

3. Source the environment: source /opt/ros/humble/setup.bash source install/setup.bash

🎮 Usage

Launch the entire software stack (Gazebo Simulation, Robot State Publisher, Bridge, SLAM Toolbox, RViz2, and the Autonomous Control Node) with a single command: Bash ros2 launch qbot_scanner qbot_bringup.launch.py

What to Expect:

The Qbot will spawn in the Ignition Gazebo world facing the central object.

It will drive forward at 0.15 m/s until it reaches the calculated optimal scanning radius.

It will lock onto the object and execute a continuous, smooth orbit.

In RViz, you will see the 2D map generating, the TF tree actively updating, and the 3D Point Cloud capturing the object.

After exactly 3 complete laps, the robot will safely park itself and terminate movement commands.

📁 Repository Structure

Qbot--3D-object-mapping/
│
├── media/                       # images and videos of the simulations
├── weekly_reports/              # weekly reports 
├── simulation/                  # Main ROS 2 Workspace
│   ├── src/
│   │   └── qbot_scanner/        # Custom Python Package
│   │       ├── config/          # SLAM and RViz parameters
│   │       ├── launch/          # Master bringup files
│   │       ├── qbot_scanner/    # Control logic (scan_logic.py)
│   │       ├── urdf/            # Robot physical description
│   │       └── worlds/          # Ignition Gazebo environments
│   │
│   └── README.md                # You are here!
│
└── .gitignore                   # Keeps the repo clean from b