Development and Implementation of a ROS-Based Differential Drive Robot for Autonomous Navigation

Abstract

The development of autonomous mobile robots has gained significant attention due to their potential applications in navigation, surveillance and industrial automation. However, achieving precise localization and obstacle avoidance in dynamic environments remains a challenge, particularly for differential drive robots. This study focuses on the development of a ROS-based differential drive robot designed for autonomous navigation. The robot is equipped with a Teensy microcontroller, DC motors with encoders for motion control, an RPLIDAR A1 for mapping and obstacle detection and a GY-85 IMU for inertial sensing and orientation estimation. To address the challenges of localization and navigation, the system integrates ROS-based software packages for sensor data processing, motion control, and real-time path planning. The navigation framework employs a proportional-integral-derivative control strategy to ensure smooth and accurate movement. Additionally, simultaneous localization and mapping techniques are used to construct real-time maps of the environment while enabling autonomous path execution. Experimental evaluations demonstrate the robot’s ability to navigate predefined environments efficiently while avoiding obstacles. Preliminary results indicate that the system achieves reliable localization with minimal drift and effective trajectory tracking with position errors of 5.5-12.5 cm with traveled times of 96-123 s. This study contributes to the field of autonomous robotics by presenting a robust and adaptable navigation framework for differential drive robots. The findings highlight the effectiveness of ROS-based integration for autonomous navigation and provide insights into potential improvements for enhancing real-time decision-making, mapping accuracy and system robustness in complex environments