Trajectory Tracking and Obstacle Avoidance with Turtlebot 3 Burger and ROS 2

Abstract

The paper presents the implementation of trajectory tracking and obstacle avoidance algorithms on a Turtlebot 3 Burger using the ROS 2 operating system. A proportional control with compensation is used for lemniscate and circle trajectory tracking. In addition, an potential artificial field (APF) algorithm is incorporated for obstacle avoidance in dynamic environments. In this approach, the robot is modeled as a particle immersed in a potential field that uses attractive functions to reach a destination point and repulsive functions to go around obstacles. Simulated tests in Gazebo software and experimental tests are performed to validate the performance of the algorithms. The results showed that the route followed meets the requirements of the problem, confirming that the proposed route planning approach is efficient.