Non-contact control method of bionic manipulator based on learning of hand motion gestures

A technology of movement posture and control method, which is applied in the direction of manipulators, program-controlled manipulators, manufacturing tools, etc., and can solve problems such as inability to apply bionic dexterous hands

Active Publication Date: 2017-01-25
DALIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It avoids the limitations of wearing devices such as data gloves, and solves the problem that the existing sensor-based control method can only obtain the pose of some joints of the hand, and cannot be applied to bionic dexterous hands with high degrees of freedom.

Method used

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  • Non-contact control method of bionic manipulator based on learning of hand motion gestures
  • Non-contact control method of bionic manipulator based on learning of hand motion gestures
  • Non-contact control method of bionic manipulator based on learning of hand motion gestures

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Experimental program
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Effect test

Embodiment

[0103] Kinect2.0 is used as the acquisition device to acquire RGB-D images, and the acquired images are transmitted to the computer through the USB interface. The manipulator used is the SCHUNK SVH five-finger bionic manipulator.

[0104] Step 1, get the RGB-D image, where the color image is C, and the depth image is D.

[0105] Step 2, initialize parameters. Frame number frame=1, hand scale parameter (hand length L hand ,width Hand posture parameters (θ mcp_fe ,θ pip ,θ mcp_aa ) k , where k={1,2,3,4,5} corresponds to the five fingers from the little finger to the thumb respectively.

[0106] Step 3, if frame=1, go to step 4, otherwise go to step 5.

[0107] Step 4, detect the hand area I and build a two-dimensional hand model C I and 3D model C H , including the following steps:

[0108] Step 4.1, obtain the binarized hand region image I according to formula (13);

[0109] Step 4.2, use the Sobel operator to extract the hand contour from the image I, calculate th...

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Abstract

The invention provides a non-contact control method for controlling a five-finger bionic manipulator through learning hand motion gestures and belongs to the field of intelligent control. According to the method, a three-dimensional hand modeling method with adaptivity is proposed, motion gestures of all joint points of a hand of a control worker are tracked according to a three-dimensional hand model, and a corresponding relationship between the motion gestures of the hand and action commands of the manipulator is established with a mapping algorithm, so that the control worker controls the five-finger manipulator in a natural mode. Under the condition of utilization of RGB-D images, the three-dimensional hand model is established to describe pose parameters of the joints of the hand, an improved APSO (adaptive particle swarm optimization) algorithm is proposed to solve the pose parameters, the rate of convergence of solution of high-dimensional parameters is effectively increased, limitation of wearable devices such as data gloves and the like is avoided, and the defects that a conventional control method based on a sensor can only acquires poses of part of joints of the hand and cannot be applicable to a bionic multi-fingered hand with high degree of freedom are overcome.

Description

technical field [0001] The invention belongs to the field of intelligent control, and relates to a non-contact control method for controlling a five-finger bionic manipulator by learning the motion posture of a human hand by using an RGB-D image as an input signal. Background technique [0002] With the continuous expansion of the application scope of robots, robots are playing an increasingly important role in the fields of industrial control and virtual assembly. At the same time, the scenarios and tasks of robot operations are becoming more and more complex. The robot's manipulator is the main device and tool for it to complete various tasks. Simple clamping devices and two-finger manipulators can no longer meet these application requirements. Manipulators are gradually developing into multi-finger, multi-joint and multi-degree-of-freedom mechanical dexterous hands. Although the current five-finger bionic mechanical dexterous hand is getting closer and closer to the human...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/22B25J13/08G06K9/00G06T7/20
CPCB25J9/163B25J9/1697B25J13/08G06V40/107
Inventor 孙怡屈雯魏诗白徐方杨奇峰
Owner DALIAN UNIV OF TECH
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