Multi-dimensional force sensor calibration experiment data fitting method based on genetic algorithm

A multi-dimensional force sensor and genetic algorithm technology, applied in the field of multi-dimensional force sensor calibration experiment data fitting, can solve problems such as optimal solution offset and limited numerical accuracy, and achieve the effects of accurate and effective results and simple and reliable algorithms

Active Publication Date: 2016-06-08
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is that the numerical accuracy of the existing data fitting method is limited in the calculation process, and the local optimal solution is generated due to the truncation error, resulting in the deviation of the optimal solution

Method used

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  • Multi-dimensional force sensor calibration experiment data fitting method based on genetic algorithm
  • Multi-dimensional force sensor calibration experiment data fitting method based on genetic algorithm
  • Multi-dimensional force sensor calibration experiment data fitting method based on genetic algorithm

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Embodiment 1

[0091] Taking the cross-beam type six-dimensional force sensor developed by Jiangsu Key Laboratory of Remote Measurement and Control Technology of Southeast University as an example, the data fitting problem in the coupling error modeling of sensor decoupling calculation is studied.

[0092] The elastic body of the multi-dimensional force sensor adopts an integral spoke-type cross beam structure, and a full-bridge circuit is formed by strain gauges attached to the front, back and side of the cross beam, and the strain generated when the elastic body is subjected to force / torque is converted into a differential output voltage value .

[0093] Such as image 3 As shown, it is a static calibration experimental device of the present invention, which consists of a force transmission shaft 1, a force column 2, a sensor 3, a dial 4, a left sliding rod 5, a right sliding rod 6, a pulley 7, a test bench base 8, an additional Pulley bar 9 forms.

[0094] The sensor 3 is fixed on a sca...

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Abstract

The invention discloses a multi-dimensional force sensor calibration experiment data fitting method based on a genetic algorithm. The method comprises the following steps: (1) carrying out a multi-dimensional force sensor static calibration experiment, and recording each dimension of input force / torque value of a multi-dimensional force sensor and each path of output voltage value under the action of the input force / torque value respectively; (2) deducing a coefficient solution formula of a sensor coupling error theoretical model; and (3) solving the error coefficient solution formula in the step (2) based on the genetic algorithm by using MATLAB (Matrix Laboratory) software, and outputting an undetermined coefficient solution of global optimum. According to the multi-dimensional force sensor calibration experiment data fitting method based on the genetic algorithm, random global search and optimization of the genetic algorithm can be used for data fitting of the multi-dimensional force sensor calibration experiment; the algorithm is simple and reliable and a result is accurate and effective; and a self-adaptive searching process of an optimal fitting curve of the experiment data is finished, so that the precision of a decoupling algorithm is improved.

Description

technical field [0001] The invention belongs to the technical field of sensors, and relates to a multi-dimensional force sensor calibration experiment data fitting method. It is specifically applicable to solving the error model fitting coefficient in the process of sensor decoupling and improving the accuracy of the sensor decoupling algorithm. Background technique [0002] The multi-dimensional force sensor is often mounted on the front end of the manipulator or the end of the manipulator claw, which is used to simultaneously detect all the component information of the multi-dimensional force / torque in space, and feed back to the robot force control system to realize the control of the force / position of the intelligent robot and ensure the operation of the robot Safe and perfect operation is the most critical type of sensor used in robots, and it is the basis and support for intelligent decision-making and control of robots. [0003] In the static calibration experiment o...

Claims

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Application Information

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IPC IPC(8): G01L25/00G06N3/12
CPCG01L25/00G06N3/12
Inventor 宋爱国李昂李会军张强冷明鑫徐宝国
Owner SOUTHEAST UNIV
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