Localization Technology Development and Implementation

Overview

This repository contains the code and documentation for a self-localization and navigation system developed for a ground robot. The system leverages onboard sensors to enable autonomous navigation, utilizing advanced technologies and tools for robust performance.

Project Description

• System Development: Created a system for self-localization and autonomous navigation using onboard sensors.
• Technology Integration: Employed Micro ROS and the Rosserial library to interface sensors with ESP32 and Arduino for low-level control.
• Tools and Technologies:
  • ROS2 (Robot Operating System 2)
  • OpenCV
  • SLAM (Simultaneous Localization and Mapping)
  • Navigation Algorithms

Features

• Autonomous Navigation: Enables the robot to navigate independently using sensor data for localization.
• Sensor Integration: Interfaces with sensors through ESP32 and Arduino using Micro ROS and Rosserial.
• Advanced Algorithms: Utilizes ROS2, OpenCV, and SLAM for efficient mapping and navigation.

Repository Contents

• src/: Source code for the localization and navigation system.
• config/: Configuration files for system setup and parameter tuning.
• docs/: Documentation including setup instructions, usage guidelines, and system architecture.
• examples/: Sample code and example configurations demonstrating system functionality.

Installation

1. Make a src folder: Make a source folder in you workspace

   mkdir src
   cd src

2. Clone the Repository:

   git clone https://github.com/Vedhamshbode/bbot_description.git

3. Install Dependencies: Ensure you have ROS2, OpenCV, and other required libraries installed on your system. Follow the installation instructions provided in the docs/ directory.
4. Build the Project: Navigate to the workspace and build the project:

   colcon build

5. Setup and Configuration: Modify the configuration files in the config/ directory as needed to match your hardware setup. For example, you may need to adjust the sensor calibration parameters.

Usage

1. Launch the system:

   ros2 launch bbot_description launch_sim.launch.py

2. Monitor and Control: Use ROS2 tools and interfaces to monitor the robot’s status and control its navigation. For example, you can visualize the robot’s path using:

   ros2 run rviz2 rviz2