THE UNIVERSITY OF DANANG
UNIVERSITY OF SCIENCE AND TECHNOLOGY
Faculty of Mechanical Engineering
Instructor: DR. PHAM ANH DUC
Student: NGUYEN VAN THANH
Student: PHAN DANG DANH
Class: 21CDTCLC1 (21.Nh05)
Table of Contents
CHAPTER 1: OVERVIEW OF THE TOPIC AND OBJECTIVES OF THE PROJECT
- 1.1. Overview of the Topic
- 1.1.1. Overview of Autonomous Robots
- 1.1.2. Overview of Lidar Technology
- 1.2. Objectives of the Project
- 1.3. Research Content
- 1.3.1. Research Subjects and Scope
- 1.3.2. Research Directions and Implementation
- 1.4. Conclusion of Chapter 1
CHAPTER 2: THEORETICAL BACKGROUND
- 2.1. Overview of Robot Operating System (ROS)
- 2.1.1. Introduction to ROS
- 2.1.2. Structure of ROS
- 2.1.2.1. ROS Filesystem Level
- 2.1.2.2. ROS Computation Graph Level
- 2.1.2.3. ROS Community Level
- 2.1.3. ROS Noetic Version
- 2.2. Hector SLAM Mapping Method
- 2.2.1. Overview of the Hector SLAM Algorithm
- 2.2.2. Hector SLAM Preprocessing
- 2.2.3. Scan Matching
- 2.3. Robot Localization Method on the Map
- 2.4. Dijkstra's Algorithm for Optimal Path Finding
- 2.4.1. Introduction to Dijkstra's Algorithm
- 2.4.2. Algorithm Description
- 2.4.3. Using the Algorithm for Robots
- 2.5. DWA Algorithm for Random Obstacle Avoidance
Project Summary
Autonomous robots have become a familiar presence in our daily lives, appearing everywhere from rural areas to urban environments, in factories and households, and playing a significant role in both industrial production and everyday activities. These robots greatly assist in replacing humans for difficult and labor-intensive tasks, thereby saving time, resources, and human effort.
Inspired by their wide-ranging applications and practical benefits, this project focuses on developing an autonomous robot capable of performing tasks fully autonomously or semi-autonomously. The project involves several key components:
Firstly, the design of robust hardware to support the robot's movement and positioning capabilities in a given space. Secondly, developing the robot's ability to create maps and accurately locate itself within those mapped environments. Following this, we implement a path-planning method for the robot to autonomously navigate and avoid obstacles. Finally, we integrate a range of applications, such as allowing the robot to move efficiently within dynamic settings.
The results of this project are promising. The robot successfully maps an unknown environment with minimal deviation and demonstrates a reliable self-localization capability, efficiently navigating to its target with minimal errors. Throughout this development process, I was guided and supported by Dr. Pham Anh Duc, whose expertise was invaluable in achieving these outcomes.
CHAPTER 1: OVERVIEW OF THE TOPIC AND OBJECTIVES OF THE PROJECT
Chapter 2: Theoretical Foundations
2. Overview of the Robot Operating System (ROS)
- 2.1. Introduction to ROS
- 2.1.1. Structure of ROS
- 2.1.2. ROS Noetic Version
2.1 Introduction to ROS (Robot Operating System)
Robot Operating System (ROS) is an open-source operating system for robots, widely used in the field of robotics with numerous advantages.
ROS is a set of tools, libraries, and conventions aimed at simplifying the task of creating complex and powerful robot behaviors across various robotic platforms without requiring significant changes to the software program.
Overview of Robot Operating System
Robot Operating System (ROS) is an open-source framework designed for robotics, providing a comprehensive suite of tools, libraries, and conventions to simplify the development of complex and powerful robotic behaviors across various platforms. ROS aims to facilitate the easy sharing and reuse of software across different robotic hardware without needing to rebuild from scratch. Rebuilding a specific robotic platform from the ground up can be time-consuming and labor-intensive. Furthermore, leveraging previous research results to develop advanced algorithms can be challenging.
The benefits provided by ROS have led to a wealth of resources in both hardware and software from research organizations worldwide. Many companies and institutions have adopted this framework to create higher-quality products. As a result, numerous devices globally now support the ROS framework.
Being an open-source system, ROS attracts significant community interest, leading to the development of a rich ecosystem of tools and libraries. Currently, ROS operates exclusively on Unix-based platforms, with software primarily tested on Ubuntu and Mac OS X. The core components, utilities, and libraries of ROS are released in versions known as ROS Distributions. These distributions are akin to Linux Distributions and provide a series of compatible software packages.
When applied to robotics, ROS reduces the technical workload for basic tasks, allowing more focus on system building and specialized research. This shift enables researchers and developers to dedicate their efforts to advanced applications and projects with higher scientific value.