Abstract
This paper presents the research and construction of a motion tracing control system for omnidirectional mobile robots based on reinforcement learning techniques in automatic control. The process of controlling a mobile robot in a flat environment with definite and unknown obstacles, taking into account the nonlinear factor of interference. Research and application of programming tools are operating systems for mobile robots (Robot Operating System - ROS). From updated information on maps, operating environment, robot control position, and obstacle identification (SLAM) to calculate the movement trajectory of a three-wheeled omnidirectional mobile robot. The positioning system calculates the orbital tracking for the robot based on the Q-learning algorithm. The results of simulation research in the Gazebo environment and running tests on real Turtlebot mobile robots have shown the practical effectiveness of the research problem of tracking motion tracking and intelligent navigation for mobile robots.
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