Autonomous navigation

Nahun Alejandro Garcia Banegas

Download Paper | Permalink

Conference: 2025 ASEE PSW Conference
Location: California Polytechnic University, California
Publication Date: April 10, 2025
Start Date: April 10, 2025
End Date: April 12, 2025
DOI: 10.18260/1-2--55164
Permanent URL: https://peer.asee.org/55164

Paper Authors

author page

Nahun Alejandro Garcia Banegas Cal Poly Pomona

Download Paper | Permalink

Abstract

Autonomous vehicles have revolutionized industries ranging from transportation and logistics to agriculture and healthcare. This vast rage of applications highlights their immense potential in our current society. With the ability to navigate complex environments, perform tasks with high efficiency, and reduce human intervention, autonomous robots have become a cornerstone of technological advancement. Inspired by these applications, the objective of this project is to design and develop a differential drive autonomous robot leveraging SLAM (Simultaneous Localization and Mapping) and various path-finding algorithms. The primary goal is to demonstrate the robot’s ability to autonomously navigate dynamic environments while maintaining real-time localization, constructing accurate maps, and effectively planning collision-free paths. The project is centered around the implementation of SLAM, a critical technology enabling robots to create and update maps of unknown environments while simultaneously tracking its position within the environment. SLAM ensures that the robot can operate in environments without prior knowledge of the surrounding. This makes SLAM adaptable tool for a wide range of real-world applications. By utilizing ROS 2's Navigation 2 (Nav2) package, this project integrates state-of-the-art tools for autonomous navigation, including the use of sensor fusion for robust data processing, behavior trees for task planning, and modular control nodes for adaptive real time navigation. The robot built uses a LiDAR sensor, to capture environmental data and process it in real time for localization and mapping tasks. Pathfinding is another critical component of this project. By incorporating various algorithms such as A*, Dijkstra’s algorithm, and Rapidly-exploring Random Trees (RRT), the robot is equipped to identify optimal paths to reach its target efficiently while avoiding obstacles and taking into consideration the unpredictability of the environment. These algorithms are evaluated and tested under different scenarios to analyze their effectiveness in dynamic and control environments. This comparison enables the selection of the most suitable algorithm for specific real-world applications, ensuring both robustness and efficiency in navigation. The design of the differential drive vehicle helps to enhances the robot’s maneuverability. With two independently driven wheels mounted on the same axis, the robot achieves precise control over its movement, making it ideal for confined spaces and intricate navigation tasks. The kinematics of the differential drive system are optimized to ensure smooth and reliable operation, while the integration of encoders allows for accurate motion control and odometry. The motivation behind this project comes from the vast potential appliations autonomous vehicles have across numerous fields. From autonomous delivery robots enhancing last-mile logistics to assisting elderly persons in an airport, the societal impact of autonomous navigation is very deep and diverse. This project seeks to explore these possibilities by providing a scalable and flexible platform for future development. Furthermore, the use of open-source tools like ROS 2 helps to reduces development costs and makes it available for the public. Through continuous testing and iterative development, the robot is expected to achieve real-time autonomous navigation capabilities, demonstrating the effectiveness of integrating SLAM with advanced path planning algorithms. This project serves as a step towards understanding and implementing core principles in autonomous robotics while contributing to the growing body of knowledge in this transformative field. By bridging theoretical concepts with practical implementation, it underscores the role of autonomous systems in addressing real-world challenges and advancing technology for societal benefit.

Citation
Format

Garcia Banegas, N. A. (2025, April), Autonomous navigation Paper presented at 2025 ASEE PSW Conference, California Polytechnic University, California. 10.18260/1-2--55164

TY - CPAPER
AB - Autonomous vehicles have revolutionized industries ranging from transportation and logistics to agriculture and healthcare. This vast rage of applications highlights their immense potential in our current society. With the ability to navigate complex environments, perform tasks with high efficiency, and reduce human intervention, autonomous robots have become a cornerstone of technological advancement. Inspired by these applications, the objective of this project is to design and develop a differential drive autonomous robot leveraging SLAM (Simultaneous Localization and Mapping) and various path-finding algorithms. The primary goal is to demonstrate the robot’s ability to autonomously navigate dynamic environments while maintaining real-time localization, constructing accurate maps, and effectively planning collision-free paths.
The project is centered around the implementation of SLAM, a critical technology enabling robots to create and update maps of unknown environments while simultaneously tracking its position within the environment. SLAM ensures that the robot can operate in environments without prior knowledge of the surrounding. This makes SLAM adaptable tool for a wide range of real-world applications. By utilizing ROS 2&#39;s Navigation 2 (Nav2) package, this project integrates state-of-the-art tools for autonomous navigation, including the use of sensor fusion for robust data processing, behavior trees for task planning, and modular control nodes for adaptive real time navigation. The robot built uses a LiDAR sensor, to capture environmental data and process it in real time for localization and mapping tasks.
Pathfinding is another critical component of this project. By incorporating various algorithms such as A*, Dijkstra’s algorithm, and Rapidly-exploring Random Trees (RRT), the robot is equipped to identify optimal paths to reach its target efficiently while avoiding obstacles and taking into consideration the unpredictability of the environment. These algorithms are evaluated and tested under different scenarios to analyze their effectiveness in dynamic and control environments. This comparison enables the selection of the most suitable algorithm for specific real-world applications, ensuring both robustness and efficiency in navigation.
The design of the differential drive vehicle helps to enhances the robot’s maneuverability. With two independently driven wheels mounted on the same axis, the robot achieves precise control over its movement, making it ideal for confined spaces and intricate navigation tasks. The kinematics of the differential drive system are optimized to ensure smooth and reliable operation, while the integration of encoders allows for accurate motion control and odometry.
The motivation behind this project comes from the vast potential appliations autonomous vehicles have across numerous fields. From autonomous delivery robots enhancing last-mile logistics to assisting elderly persons in an airport, the societal impact of autonomous navigation is very deep and diverse. This project seeks to explore these possibilities by providing a scalable and flexible platform for future development. Furthermore, the use of open-source tools like ROS 2 helps to reduces development costs and makes it available for the public.
Through continuous testing and iterative development, the robot is expected to achieve real-time autonomous navigation capabilities, demonstrating the effectiveness of integrating SLAM with advanced path planning algorithms. This project serves as a step towards understanding and implementing core principles in autonomous robotics while contributing to the growing body of knowledge in this transformative field. By bridging theoretical concepts with practical implementation, it underscores the role of autonomous systems in addressing real-world challenges and advancing technology for societal benefit.

AU - Nahun Alejandro Garcia Banegas
CY - California Polytechnic University, California
DA - 2025/04/10
PB - ASEE Conferences
TI - Autonomous navigation
UR - https://peer.asee.org/55164
DO - 10.18260/1-2--55164
ER -