A Robot Path Tracking Algorithm Based on Potential Energy Field

Abstract

The invention provides a potential-energy-field-based robot path tracking algorithm. The algorithm comprises: (1), a turning radius is obtained; (2), on the basis of the turning radius R and a current linear velocity Vx(t), a linear velocity Vx(t+1) at a next time is estimated; and (3), according to the R and the Vx(t+1), an angular velocity omega is calculated, a reasonable path tracking velocity (Vx, omega) is obtained, and then fitting is carried out on an obtained current path and a preset path to obtain an optimal path tracking velocity (Vx, omega optimal), thereby determining an optimal tracking path track. According to the invention, the basic velocity decomposition value (Vx, omega) is obtained based on analysis and calculation on the real-virtual path of the robot; and then the optimal path is predicted by the robot path in the potential energy field, so that the calculation efficiency is improved substantially and the requirement on the computer hardware is reduced. Moreover, no matter how the characteristics of the system or how large the initial deviation angel of the robot relative o the preset path is, convergence of the robot to the preset path can be guaranteed by the algorithm.

Description

technical field [0001] The invention relates to a path tracking algorithm, in particular to a robot path tracking algorithm based on a potential energy field. Background technique [0002] The path tracking algorithm is to limit the trajectory of the mobile robot to the acceptable error range on the established path. [0003] At present, the commonly used mobile robots plan the trajectory of the robot through magnetic strips or color strips, and the robot detects the error between the actual trajectory of the robot and the predetermined trajectory through a magnetic sensor probe or a photoelectric sensor array. The error detected by the sensor is input to the motion control unit as feedback, and when the error is zero, the robot is on the predetermined track. This is a natural application of linear control theory, and most controllers are implemented in the form of PID. [0004] Another common robot path tracking method is to calculate the Manhattan distance from a preset ...

AI Technical Summary

Problems solved by technology

However, this method has a large amount of calculation and the search range cannot be controlled. It can only search for all possible speeds (Vx, ω) of the robot, and the requirements for computer hardware are relatively high.

And a major disadvantage is that when the deviation between the robot’s position angle and the current preset path is too large, the robot can’t correct the angle only through the combination of (Vx, ω), which will eventually cause the robot to deviate from the preset path

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