Mechanical arm point-to-point trajectory planning method and device based on radial basis function

Abstract

The embodiment of the invention provides a mechanical arm point-to-point trajectory planning method based on a radial basis function. The method comprises the steps of constructing a motion trajectory of a mechanical arm by adopting a Gaussian radial basis function; and constructing a corresponding optimization target equation according to parameters of the radial basis function, and optimizing the time of the whole trajectory. According to the method of the invention, the smooth motion trajectory can be generated between any target points, and any order derivative of the trajectory is continuous and is not influenced by the number of the target points. Meanwhile, the generated trajectory is simple in form and small in calculated amount, important parameters such as acceleration and jerk of the trajectory can be optimized through unified parameters, the smoothness of the trajectory is improved, then the running time of the whole trajectory is shortened, and the smoothness and working efficiency of the mechanical arm are improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method and device for point-to-point trajectory planning of a manipulator based on radial basis functions. Background technique [0002] As a highly automated and intelligent device, robotic arms have been widely used in industrial scenarios. In these work scenarios, the work of the manipulator is to move from the initial point to the target point through its end effector, and then complete the specified task, so the movement of the manipulator can be simplified as a series of point-to-point movements. The goal of trajectory planning is to connect these points with a smooth motion trajectory. However, a good trajectory planning needs not only to ensure the continuity of the trajectory position, but also to ensure the continuity of the high-order derivatives of the trajectory such as velocity, acceleration and jerk (first-order derivative of acceleration), otherwise...

AI Technical Summary

Problems solved by technology

In this type of method, the cubic spline function can only ensure the continuity of speed and acceleration, and it is difficult to improve the performance of the manipulator. In the actual application of the manipulator, it often causes the vibration of the manipulator.

For the quintic spline curve, because the order of the polynomial is too high, the speed, acceleration and other important parameters of the trajectory change too fast, resulting in unstable operation of the manipulator

3. Another method is the trajectory planning method based on B-splines. This method changes the shape of the curve through the control nodes, but the curve parameters are numerous and difficult to set, and the control points need to be back-calculated based on the target points, which is complex in theory and The amount of calculation is large, and the continuous order inside the trajectory is usually limited, which is very inconvenient in actual use

[0004] At the same time, these methods are difficult to adjust the important parameters of the trajectory such as the acceleration and jerk of the trajectory by adjusting simple parameters. It is often necessary to change the position of the target point to find a satisfactory trajectory through trial and error. Not only the steps are cumbersome, but the final effect also difficult to guarantee

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