Incomplete constraint wheeled robot locus tracking control method based on look-up table method

Abstract

The invention belongs to the technical field of robots, and discloses an incomplete constraint wheeled robot locus tracking control method based on a look-up table method. The method comprises the steps: solving a robot kinematic model through an Euler numerical value, and building a movement locus (x, y) relation table between system input (v, omega) and the robot under the condition of saturation constraint; determining a control input quantity according to a proposed shortest Euclidean distance criterion look-up table; finally employing the determined control input quantity for the robot, and enabling the movement locus of the robot to be tracked to a specific reference locus. The effectiveness of the method provided by the invention is verified based on Matlab through the tracking simulation results of linear, sine, cosine and circular loci.

Description

technical field [0001] The invention belongs to the technical field of robots, and in particular relates to a trajectory tracking control method for an incomplete constrained wheeled robot based on a look-up table method. Background technique [0002] With the development of science and technology, mobile robots have been widely used in many fields such as agriculture and industry, and mobile robots have become a hot research topic in recent years. The control problem of wheeled mobile robots has attracted a large number of researchers due to its theoretical challenges and wide practical application value. The existing technology is aimed at the trajectory control problem of mobile robots, especially a series of coordinate sequence trajectories whose specified reference trajectory has strong nonlinearity or does not meet the description of a single curve, and the effect on trajectory tracking is poor. Wheeled mobile robots are constrained by pure rolling, which is a typical...

AI Technical Summary

Problems solved by technology

In practical application, there are several deficiencies: 1) It is difficult to give an accurate function description model of the desired trajectory curve

This brings difficulties to the choice of which control method and the calculation of control parameters after the control method is selected

2) For reference trajectories with different characteristics, the robustness of the existing technology is poor, and the trajectory tracking control error is large

Due to different tasks at different times (tasks are temporary and random), the expected trajectory of the robot yesterday, today, and tomorrow is not exactly the same. It is necessary to choose a suitable trajectory tracking control method, which is undoubtedly a difficult task for the user. Work

3) The control algorithm has complex structure, high cost and poor real-time performance

There are many existing trajectory control technologies. In order to pursue breakthroughs in control accuracy and robustness, a large number of uncertain factors are added to the model analysis, such as parameter uncertainty, load uncertainty, and modeling error in the motion consideration model. , the proposed trajectory controller has a complex structure and a large amount of calculation

In some state feedback trajectory controllers, it is necessary to detect the attitude information such as the linear velocity, angular velocity, and position of the wheeled mobile robot in real time, and it is necessary to install sensors and communicate with the main controller. The cost is high and the real-time performance is poor

[0003] To sum up, the problem existing in the prior art is: for the problem that a series of coordinate sequences with strong nonlinearity or not satisfying the description of a single curve are used as reference trajectories, the prior art does not provide a simple and effective wheel formula. Trajectory control method of mobile machine

In the existing robot trajectory tracking control, the trajectory tracking control is not based on the look-up table method, resulting in poor real-time and robustness of the existing robot

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