Kinematic and Dynamic Modeling Based on Trajectory Tracking Control of Mobile Robot with Mecanum Wheels

Abstract

The trajectory tracking is important to make the WMR move autonomously from the starting point to the destination along a predefined time. Implementing of trajectory tracking control is a fundamental part to accomplish its application tasks. In this article a new method by using a hybrid controller has been presented to solve the problem of the trajectory tracking of four mecanum wheeled mobile robot. Proposed controller is depending on modeling of robot kinematic and dynamic equations. The novelty in this work is that, an optimal control system self-tuning parameters based on an optimization algorithm for these models of the mobile robot is utilized. The optimal control type that is used in this work is the Linear Quadratic Regulator (LQR) controller. LQR is used to control the actuator torque that is required in each wheel to achieve the robot task. The parameters of the LQR controller are tuned by using Ant Colony Optimization (ACO). For results simulation, MATLAB/ Simulink is used for circular and infinity shape trajectories. Results show that when the robot follows a circular trajectory, the values of position trajectory error values are reduced to small value (ex=3.218 *10-5m) and (ey= 2.224*10-5m) in xo and yo directions, respectively and remained almost at these values until the end of the simulation time. The maximum orientation error is (= 0.103rad), and convergent to zero after two seconds of the mobile robot movement. Also when the robot follows an infinity shape trajectory, the position trajectory error values are (ey) and () are reduced to small value -4.078 *10-4m and 3.174*10-4rad respectively, while, (ex) is reduced to 5.263*10-4 m after about 15 seconds.

Keywords

• ant colony optimization
• linear quadratic regulator controller
• robot kinematics: trajectory tracking
• wheeled mobile robot