| Autonomous mobile robots are a classic category in the field of robots.They are widely used in industry,commerce,agriculture,national defense security and aerospace.Their motion control research,especially tracking control,has attracted wide attention from academia.For example,in logistics and transportation systems,wheeled mobile robots have fast and accurate path tracking control when the path is known.The key technology of logistics system automation.Therefore,this paper mainly studies the tracking control method of autonomous mobile robot theoretically and experimentally.In the part of theoretical research,firstly,the kinematics model of autonomous mobile robot is established and its correctness is verified;secondly,the pose error model of autonomous mobile robot is deduced based on the model.On this basis,a robot tracking controller based on sliding mode control method is designed.The simulation results show that the sliding mode controller can only perform well on simple trajectories such as straight lines and arcs of the robot.Model predictive control(MPC)is a control method which does not depend on precise mathematical model and has real-time rolling optimization.So this paper designs a model predictive tracking controller based on robot pose error model,and carries out simulation analysis.The application effect of the two controllers in robot tracking control is analyzed.By comprehensive analysis,it can be found that the model predictive tracking controller has better adaptability to complex paths than the sliding mode tracking controller.On the basis of the above theoretical analysis,the experimental verification is carried out.Firstly,the software transplantation of the lower computer system of the actual wheeled mobile robot platform is realized.At the same time,the embedded model predictive controller software and communication program are designed.Then,aiming at the shortcomings of the existing autonomous mobile robot platform in the laboratory,the corresponding transformation is carried out,mainly including the transformation of communication module and motor drive.Module modification,redesign of upper and lower computer programs,and design of a wheeled mobile robot state information acquisition system based on vision and image processing.After the above modification and design,embedded model predictive controller software is applied to the experimental platform of the autonomous mobile robot after the transformation,and the Institute is verified by tracking experiments on any given reference trajectory.Effectiveness of the design controller.Combined with theoretical research and experimental verification,it can be found that the designed model predictive tracking controller has certain theoretical research value,and can be effectively applied to the actual wheeled mobile robot platform,which has certain engineering application prospects. |
