Motion Control Technology Of Wheeled Mobile Robot With Vision Navigation

As a kind of wheeled mobile robot, Automated Guided Vehicle (AGV) has been used widely in manufacturing, automotive, electronics, paper, tobacco, pharmaceutical, food and other industries for automated material transportation, and there is a great demand for AGV product in the domestic and international markets. Developing a high-performance AGV with independent intellectual property rights has a great theoretical significance and engineering value.Vision-based tracking navigation only needs to identify guiding lines preset manually, which can achieve a very high accuracy and real-time. Two-wheel differential driving can make AGV turnaround at a zero radius, which shows a good maneuverability. This paper attempts to improve the motion control performance for an AGV with vision navigation and differential turnaround in the perspective of integrating theoretical research with technology development.At the level of theoretical research, two main technical guidelines on how to correct pose errors of AGV by adjusting speed difference output and how to eliminate speed error of driving wheel by regulating voltage output are followed. This paper has made an intensive research on path tracking algorithm with the limited control capability and servo control algorithm able to implement tracking output. Firstly, three kinds of motion control approaches for mobile robots, including kinematics, dynamics, and kinematics with control constraints are compared. A hybrid motion control model containing path tracking and servo control is presented. Speed and acceleration constraints and speed difference output are used to match the capability of path tracking algorithm to correct pose errors with that of servo control algorithm to eliminate speed error.Secondly, path tracking of AGV is investigated. The difficulties in optimized objective selection, output beyond constraints, and control step setting are analyzed for linear quadratic regulator (LQR) and predictive control. A LQR optimal control algorithm based on multi-step motion prediction is proposed for the small error state, which uses multi-step motion control with the best coordination to reduce two pose errors synchronously, and minimizes control steps under speed and acceleration constraints to keep an achievable fastest tracking. An intelligent predictive iterative control algorithm based on state analysis of visual field is proposed for the large error state, which replaces a quadratic weighted sum function with an optimal conversion strategy of error states as a description of control objectives, and uses a synchronous control algorithm to coordinate a correction process of two pose errors for the ideal rectification state.Thirdly, servo control of driving system is discussed, in which system model identification and PID parameter tuning are both expressed as the multi-objective optimization. A kind of Pareto-type multi-objective genetic algorithm based on elitist guidance mechanism is proposed, which makes a fast, effective and directional search for Pareto optimal solutions by using these mechanisms of elitist guidance, diversity preservation and multi-population evolution, in order to meet decision-making preferences that are required by path tracking.At the level of technology development, functional modeling by using a multi-agent system view and implementation by using embedded technology is presented for motion control of AGV. An embedded system design method based on a multi-agent structure is presented, and a transformation model from a controller agent to an agent structure and task is constructed, which can provide a high -performance embedded controller for path tracking and servo control algorithms effectively.Computer numerical simulation is used to verify the feasibility of the theories proposed in this paper, and then theoretical research results are converted into a high-performance AGV vehicular controller based on embedded technology, which has been applied successfully to an AGV (named NHAGV) with vision navigation we develop independently. Many system operation tests and path tracking experiments are carried out. Experiment results have sufficiently verified the effectiveness of the control techniques and the advantages of AGV vehicular controller presented in this paper, which provides a solid technical foundation for developing a high-performance AGV vehicular controller with independent intellectual property rights.